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Text and data mining activities—that is, the automated processing of digital materials to uncover new knowledge—have become more frequent in all areas of scientific research. Because they require a massive use of copyrighted work, there are evident conflicts with copyright legislation. Countries at the forefront of research and development have begun to address this issue. This paper presents the basic aspects of legislation applicable to text and data mining activities. It offers a detailed comparative analysis of the norms of the main jurisdictions that have regulated them to date, highlighting in each case the positive and negative aspects. An adequate knowledge of these laws is not only important for researchers but also important for the academic librarians who provide advice and support in these matters. [ABSTRACT FROM AUTHOR]

Given the past limitations on clinical practice training during the COVID-19 pandemic, a hybrid format program was developed, combining a time-lapse unfolding case study and high-fidelity simulation. This study assesses the effectiveness of a new form of clinical training from the perspective of student nurses. A questionnaire was administered to 159 second-year nursing students enrolled in the "Basic Nursing Practice II" course. Text mining was performed using quantitative text analysis for the following items: (1) aspects that were learned more deeply, (2) benefits, and (3) difficulties encountered with the new practice format. The new clinical practice format enhanced participants' learning related to the daily changes required in nursing care and improved their nursing competency through simulated patient interactions. However, the participants faced difficulties dealing with patients accompanied by secular changes. Moreover, they found remote group work challenging. These findings can be applied to the development of new educational strategies. [ABSTRACT FROM AUTHOR]

Background: In Japan, over 450 public health centers played a central role in the operation of the local public health system in response to the COVID-19 pandemic. This study aimed to identify key issues for improving the system for public health centers for future pandemics. Methods: We conducted a cross-sectional study using an online questionnaire. The respondents were first line workers in public health centers or local governments during the pandemic. We solicited open-ended responses concerning improvements needed for future pandemics. Issues were identified from these descriptions using morphological analysis and a topic model with KHcoder3.0. The number of topics was estimated using Perplexity as a measure, and Latent Dirichlet Allocation for meaning identification. Results: We received open-ended responses from 784 (48.6%) of the 1,612 survey respondents, which included 111 physicians, 330 nurses, and 172 administrative staff. Morphological analysis processed these descriptions into 36,632 words. The topic model summarized them into eight issues: 1) establishment of a crisis management system, 2) division of functions among public health centers, prefectures, and medical institutions, 3) clear role distribution in public health center staff, 4) training of specialists, 5) information sharing system (information about infectious diseases and government policies), 6) response to excessive workload (support from other local governments, cooperation within public health centers, and outsourcing), 7) streamlining operations, and 8) balance with regular duties. Conclusions: This study identified key issues that need to be addressed to prepare Japan's public health centers for future pandemics. These findings are vital for discussions aimed at strengthening the public health system based on experiences from the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

In this study, we employed our previously developed data mining method to show that a thermodynamic state shift occurred preceding the 2011 Mw 9 East Japan Earthquake (GEJE), coinciding with the onset of crustal stress manifestations. Our discussion starts with the insights obtained from our prior research, which revealed that small ground vibration fluctuations (GVF) detected near the epicenter of the GEJE are thermodynamically equivalent to a cellular automaton (CA). This equivalence allowed us to consider the "Process to GEJE," defined as the transition from GVF to catastrophic rupture in the GEJE, as analogous to the nonequilibrium-to-equilibrium thermodynamic transition in the CA. Therefore, if we find a thermodynamic state shift in the CA, it is reasonable to assume that a similar thermodynamic state shift may exist in the "Process to GEJE." We successfully derived a thermodynamic state function that exhibits a significant change before the nonequilibrium-to-equilibrium thermodynamic transition in the CA. By evaluating this thermodynamic state function using the GVF data of the "Process to GEJE," we discovered its maximum value occurring on 2007-10-28 at 10:30:00 JST, 1231 days before the GEJE occurred on 2011-03-11 at 14:46 JST. This maximum value can be considered as an indication of a thermodynamic state shift prior to the GEJE. Furthermore, near the timing of the thermodynamic state shift, it has been observed that the GVF state approaches thermodynamic equilibrium and a sudden increase in crustal stress was first noted on 2007-11-22 at 18:02:44 JST. [ABSTRACT FROM AUTHOR]

BACKGROUND: Return-to-work (RTW) programs are provided as rehabilitation for people who have taken sick leave from work because of mental health problems. However, methods to present this information to workplaces objectively remain limited. OBJECTIVE: This study aimed to conduct an exploratory investigation of the relationship between duration of sick leave and time variation of words used in RTW programs for depression from textual data collected from electronic medical records as a new evaluation indicator. METHODS: The study subjects were those who had taken sick leave because of major depressive or adjustment disorder and had participated in an RTW program. The study data comprised demographic characteristics and texts. Textual data were collected from electronic medical records and classified based on the SOAP note. Thereafter, the textual data were quantified into category scores based on a standard text analysis dictionary. A generalized linear mixed model was used for the statistical analysis, with the score for each category (emotional, social, cognitive, perceptual, biological, motivational, relativity, and informal) as the dependent variable and the duration of sick leave, time, and interaction between the duration of sick leave and time as the independent variables. The level of statistical significance was set at 0.05. RESULTS: In total, 42 participants were included in the analysis. The results revealed a significant interaction between the social (p = 0.001) and emotional (p = 0.002) categories. CONCLUSION: The findings suggest a relationship between word changes in electronic medical records and the duration of sick leave. [ABSTRACT FROM AUTHOR]

Partial periodic pattern (3P) mining is a vital data mining technique that aims to discover all interesting patterns that have exhibited partial periodic behavior in temporal databases. Previous studies have primarily focused on identifying 3Ps only in row temporal databases. One can not ignore the existence of 3Ps in columnar temporal databases as many real-world applications, such as Facebook and Adobe, employ them to store their big data. This paper proposes an efficient single database scan algorithm, Partial Periodic Pattern-Equivalence Class Transformation (3P-ECLAT), to identify all 3Ps in a columnar temporal database. The proposed algorithm compresses the given database into a novel list-based data structure and mines it recursively to find all 3Ps. The 3P-ECLAT leverages the "downward closure property" and "depth-first search technique" to reduce the search space and the computational cost. Extensive experiments have been conducted on synthetic and real-world databases to demonstrate the efficiency of the 3P-ECLAT algorithm. The memory and runtime results show that 3P-ECLAT outperforms its competitor considerably. Furthermore, 3P-ECLAT is highly scalable and is superior to the previous approach in handling large databases. Finally, to demonstrate the practical utility of our algorithm, we provide two real-world case studies, one on analyzing traffic congestion during disasters and another on identifying the highly polluted areas in Japan. [ABSTRACT FROM AUTHOR]

We propose a data mining method to extract physical phenomena from the ground vibration velocity fluctuation (GVF) which is a daily observed weak signal and has no specific waveform. Our aim is to detect any traces of the return of ground motion to its normal state after earthquakes, and the evolution of ground motion towards earthquakes in the GVF. We focus on the GVF recorded near the epicenter of the magnitude 9 Great East Japan Earthquake (GEJE). Although the GVF can be discussed in the framework of the master equation which represents the thermodynamics of a stochastically fluctuating non-equilibrium system, the relation between the thermodynamic parameters and seismology-related phenomena is hardly known. So, we introduce cellular automata (CA) to analogically interpret the physical phenomena of interest as thermodynamic parameters, and show the thermodynamic equivalence between GVF and CA. These CA-derived thermodynamic parameters are then expected to deliver physical phenomena similar to those of the target when evaluated on the GVF data. In the demonstrated example of data mining, the stress relaxation signal immediately after GEJE is discovered from the recorded GVF data by deriving the thermodynamic parameters representing the stress relaxation of CA and evaluating these thermodynamic parameters for the recorded GVF data. Furthermore, the elastic rigidity and viscosity of the underground structures are estimated from the stress relaxation signal. The novelty of this study lies in drawing attention to the GVF, and combining standard techniques of CA with GVF through the use of the master equation. [ABSTRACT FROM AUTHOR]

Using text mining method, this study revealed that supervisors with high work engagement frequently mentioned about information retrieval, information transmission, and carefulness in supporting their subordinates. Supervisors with high work engagement probably have active communication with their subordinates and support them on a daily basis. Objective: This study aimed to structure supervisory support and clarify the relationship between supervisors' work engagement and support for their subordinates. Methods: We conducted a cross-sectional study in a manufacturing company using a questionnaire survey. Supervisors provided open-ended responses regarding the provision of support for their subordinates. Using text mining, we structured these descriptions into multiple categories, assigned words to them, and analyzed frequently mentioned categories by the level of work engagement. Results: We obtained responses from 729 participants that included 13,968 words. We structured supervisory support by three categories (contents, direction, and attitude toward support) and 11 subcategories. As supervisors' work engagement increased, the rates of mentioning information retrieval, information transmission, and carefulness increased. Conclusions: Supervisors with work engagement could communicate with each other and be careful in providing support to their subordinates. [ABSTRACT FROM AUTHOR]

Background: The size and function of the future liver remnant (FLR) is an essential consideration for both eligibility for treatment and postoperative prognosis when planning surgical hepatectomy. Over time, a variety of preoperative FLR augmentation techniques have been investigated, from the earliest portal vein embolization (PVE) to the more recent Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and liver venous deprivation (LVD) procedures. Despite numerous publications on this topic, no bibliometric analysis has yet been conducted. Methods: Web of Science Core Collection (WoSCC) database was searched to identify studies related to preoperative FLR augmentation techniques published from 1997 to 2022. The analysis was performed using the CiteSpace [version 6.1.R6 (64-bit)] and VOSviewer [version 1.6.19]. Results: A total of 973 academic studies were published by 4431 authors from 920 institutions in 51 countries/regions. The University of Zurich was the most published institution while Japan was the most productive country. Eduardo de Santibanes had the most published articles, and Masato Nagino was the most frequently co-cited author. The most frequently published journal was HPB, and the most cited journal was Ann Surg, with 8088 citations. The main aspects of preoperative FLR augmentation technique is to enhance surgical technology, expand clinical indications, prevent and treat postoperative complications, ensure long-term survival, and evaluate the growth rate of FLR. Recently, hot keywords in this field include ALPPS, LVD, and Hepatobiliary Scintigraphy. Conclusion: This bibliometric analysis provides a comprehensive overview of preoperative FLR augmentation techniques, offering valuable insights and ideas for scholars in this field. [ABSTRACT FROM AUTHOR]

Designing an over-the-counter medication electronic health record (OTC-EHR) may help improve OTC usage. An online survey for the conceptual OTC-EHR design examined participant characteristics, attitudes towards obtaining user-shared OTC medication information, health-related application usage, and the inclination to share anonymized health information. Descriptive statistics, tests to assess statistical significance, and text mining were used to analyze the results. The findings revealed that Japanese consumers, particularly those with high eHealth literacy and women, possess relatively positive attitudes towards obtaining user-shared OTC medication information than those with low eHealth literacy (t (280.71) = −4.11, p < 0.001) and men (t (262.26) = −2.78, p = 0.006), respectively. Most consumers own smartphones but do not use health-related applications. A minority held positive attitudes about sharing anonymized health information. The perceived helpfulness of OTC-EHR was positively associated with the usage of health-related applications (χ2 (4) = 18.35, p = 0.001) and attitude towards sharing anonymized health information (χ2 (3) = 19.78, p < 0.001). The study findings contribute towards OTC-EHR's design to enhance consumers' self-medication and reduce risks, while the psychological barriers to sharing anonymized health information should be improved by increasing the OTC-EHR's penetration rate and engaging in appropriate information design. [ABSTRACT FROM AUTHOR]

Driven by deep learning, great breakthroughs had been made in the field of target detection. Small target detection algorithms were widely used in industry, agriculture and other fields. But the small target had few available features and the loss of small target detail information in feature extraction. So it led to the low accuracy of the small target detection algorithms. In this paper, we proposed DBF‐YOLO algorithm based on the classical YOLOV5. The classical YOLOV5 algorithm with high speed. The detection speed of the minimum model could reach 24 ms. However, the deep network structure led to the low detection accuracy of small targets. Our proposed DBF‐YOLO algorithm was an improvement on the problem of small target information being lost. The main contributions of this article were mainly: First, a shallow feature extraction network was introduced in P1 layer, more details of small targets could be well retained. Second, by adding the feature fusion network of shallow feature map and the detection output part in the FPN + PAN layers, the algorithm's accuracy and generalization ability were significantly enhanced. Compared to YOLOV5, the performance of the DBF‐YOLO algorithm was significantly improved. On the validation set, mAP@0.5 and mAP@0.5:0.95 were increased by 8.80 and 5.90%, respectively. Recall was increased from the initial 34.50–41.80%. Precision was increased from initial 44.20 to 50.70%. On the test set, mAP@0.5 and mAP@0.5:0.95 were increased by 6.40 and 3.90%, respectively. Recall was increased 5.10%. Precision was increased 6.60%. Experiments had shown that the improved algorithm achieved good results in accuracy. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Pedestrian detection task is generally composed of location and classification. In this work, we consider the problem of pedestrian detection under the condition of blurred pedestrian targets and small pedestrian scales. Most methods are only suitable for the detection task under ideal conditions or simply consider one of the above problems. For the sake of achieving better results, we proposed a new method that improved from both location and classification aspects. First, we propose a video‐based pedestrian detection method that generates pedestrian proposals from the static feature extraction branch and motion information extraction branch. Secondly, a two‐scale classification method is used in the structure to solve the various scale instance problem. Finally, experiments on public datasets demonstrate that this work delivers better performance than the HOG+SVM, SAF R‐CNN, and YOLO+GMM methods. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Background: Patients with heart failure (HF) often inadequately perceive their symptoms. This may be because the medical terms do not match the somatic changes experienced by patients. To improve symptom perception, healthcare professionals must understand the somatic changes as perceived by patients. Objective: This study aims to analyze patients' narratives about somatic changes in patients with HF by text mining and to clarify the overall description of somatic changes using patients' expressions. Methods: Semistructured interviews were conducted on 21 patients hospitalized for acute exacerbation of HF. Qualitative data obtained from the interviews were analyzed by content analysis through text mining. Results: Among the 21 patients, 76.2% were men. The mean (SD) age was 71.3 (13.7) years. The most frequently used terms were "breath," "distressed," "feet," and " ha-ha (gasping sound)" (46, 40, 29, and 28 times, respectively). The somatic changes noticed by patients could be categorized into medical jargon such as "dyspnea on exertion," "exercise intolerance," "fatigue," "paroxysmal nocturnal dyspnea," "frequent urination," "increased sputum," "weight gain," "feet and face edema," "abdominal edema," and "ankle edema." However, the expressions of somatic changes used by the patients were diverse. Conclusions: The findings of patient-specific expressions of symptoms suggest that there is a need to assess symptoms not only using medical jargon but also by focusing on patient-specific expressions. [ABSTRACT FROM AUTHOR]

With the development of recent economic globalization, international exchanges and cooperation are increasingly frequent and in-depth. In this process, there is a serious obstacle, that is, language differences. Therefore, the development of high-quality and practical machine translation system is of great significance. Japan has a close relationship with China, so it is necessary to acquire and process Japanese information. Japanese translation is the basis of Japanese information processing, which plays an important role in cross language information retrieval, machine translation, information extraction and other practical applications. In recent years, machine translation has made remarkable progress, but there is still much room for improvement in the quality of translation. Multimedia assisted instruction is an important application of computer technology. Therefore, this paper realizes the feature recognition and hardware structure of Japanese machine translation; for the efficient implementation of the model, the edge-driven model is combined. The proposed model is implemented through the edge devices and the performance of the model is validated through the testing. The recognition accuracy is much higher than the traditional models and the robustness is higher. [ABSTRACT FROM AUTHOR]

Introduction. The number of occupational therapists in Japan continues to increase, which has led to an urgent need to improve the educational environment for new graduate occupational therapists. This study attempted to identify the current state and challenges of the educational environment for new graduate occupational therapists in Japan. Methods. We employed a mixed method using quantitative and qualitative data from a questionnaire survey of 1055 chief occupational therapists in Japanese hospitals. The questionnaire consisted of (1) basic information about the respondent and their hospital, (2) educational environment for new graduate occupational therapists at the respondent's hospital, (3) time spent on in-hospital lectures and on-the-job training, and (4) challenges in the clinical education of new graduate occupational therapists. Text data was analysed qualitatively using text mining to create cooccurrence networks. Results. A total of 385 responses were obtained with a response rate of 36.5%. All hospitals had recruited new graduate occupational therapists in the last five years, but more than half of them did not have a philosophy and policy on education and had not prepared guidelines for the completion of occupational therapy education. The cooccurring network of issues in the educational environment for new graduate occupational therapists indicates the need to create standard guidelines, train supervisors, and develop a hospital education system. Conclusion. In the future, the needs of the educational environment for newly graduated occupational therapists should be investigated, and standardised educational guidelines should be developed. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has spurred the growth of a global infodemic. In order to combat the COVID-19 infodemic, it is necessary to understand what kinds of misinformation are spreading. Furthermore, various local factors influence how the infodemic manifests in different countries. Therefore, understanding how and why infodemics differ between countries is a matter of interest for public health. This study aims to elucidate and compare the types of COVID-19 misinformation produced from the infodemic in the US and Japan., Methods: COVID-19 fact-checking articles were obtained from the two largest publishers of fact-checking articles in each language. 1,743 US articles and 148 Japanese articles in their respective languages were gathered, with articles published between 23 January 2020 and 4 November 2022. Articles were analyzed using the free text mining software KH Coder. Exploration of frequently-occurring words and groups of related words was carried out. Based on agglomeration plots and prior research, eight categories of misinformation were created. Lastly, coding rules were created for these eight categories, and a chi-squared test was performed to compare the two datasets., Results: Overall, the most frequent words in both languages were related to health-related terms, but the Japan dataset had more words referring to foreign countries. Among the eight categories, differences with chi-squared p ≤ 0.01 were found after Holm-Bonferroni p value adjustment for the proportions of misinformation regarding statistics (US 40.0% vs. JP 25.7%, ϕ 0.0792); origin of the virus and resultant discrimination (US 7.0% vs. JP 20.3%, ϕ 0.1311); and COVID-19 disease severity, treatment, or testing (US 32.6% vs. JP 45.9%, ϕ 0.0756)., Conclusions: Local contextual factors were found that likely influenced the infodemic in both countries; representations of these factors include societal polarization in the US and the HPV vaccine scare in Japan. It is possible that Japan's relative resistance to misinformation affects the kinds of misinformation consumed, directing attention away from conspiracy theories and towards health-related issues. However, more studies need to be done to verify whether misinformation resistance affects misinformation consumption patterns this way., (© 2024. The Author(s).)

Background: We previously reported the impact of general practice/family medicine training on postgraduate training in Japan using evaluation criteria standardized nationwide. However, there is a possibility that new insights may be gained by analyzing the reflective reports written by these residents., Methods: Junior residents who participated in one-month general practice/family medicine training at one of five medical institutions with full-time family medicine specialists between 2019 and 2022 were enrolled in this study. They were assigned to submit a reflective report on their experiences and thoughts every day during the training. We analyzed these reflective writings using text mining and created a co-occurrence network map to see the relationship between the most frequently used words., Results: Ninety junior residents participated in the study. The words that appeared most frequently in the sentences referring to clinical ability included "symptoms," "medical examination," "consultation," "treatment," and "examination." The words of "family" and "(patient) oneself" showed strong association in the co-occurrence network map., Conclusion: It was suggested that general practice/family medicine training greatly contributes to the acquisition of clinical abilities and deepens the learning of junior residents not only about patient care but also about family-oriented care.

Periodic pattern mining is an emerging technique for knowledge discovery. Most previous approaches have aimed to find only those patterns that exhibit full (or perfect) periodic behavior in databases. Consequently, the existing approaches miss interesting patterns that exhibit partial periodic behavior in a database. With this motivation, this paper proposes a novel model for finding partial periodic patterns that may exist in temporal databases. An efficient pattern-growth algorithm, called Partial Periodic Pattern-growth (3P-growth), is also presented, which can effectively find all desired patterns within a database. Substantial experiments on both real-world and synthetic databases showed that our algorithm is not only efficient in terms of memory and runtime, but is also highly scalable. Finally, the effectiveness of our patterns is demonstrated using two case studies. In the first case study, our model was employed to identify the highly polluted areas in Japan. In the second case study, our model was employed to identify the road segments on which people regularly face traffic congestion. [ABSTRACT FROM AUTHOR]

Repetitive volcanoseismic signals, including very‐long‐period signals (VLP) and long‐period signals (LP), provide a unique probe of fluid transport processes inside magmatic‐plumbing system. While syneruptive signals are often detected and analyzed with regional or/and global seismic networks to retrieve eruption location and mechanism, repetitive noneruptive volcanoseismic signals are generally small, and they are typically detected with in situ stations near the volcanic edifices. Here, we show that repetitive VLP and synchronous deformation events in Aso volcano, Japan, can be detected in the high (15–30 s) and low (50–100 s) VLP bands, respectively, at seismic stations located ∼30–1,000 km away from their sources. Changes in the polarities, phases, and amplitudes of VLP and synchronous deformation events observed at the in situ stations can be verified by the seismic waves in the two VLP bands, respectively, at distant stations up to 150 km. Forward modeling of the amplitude decay in the two VLP bands against epicentral distance corroborates the source locations previously determined by the in situ data, whereas the joint data analysis of in situ and distant stations at high VLP band suggests the presence of single‐force component (i.e., force/moment ratio of 10−4 m−1) in the source of VLPs. We advocate that not only can systematic data mining against established global and regional seismic networks potentially expand the detection capability of repetitive volcanoseismic signals backward in time when in situ observations were unavailable, but it could also substantially improve the detection and monitoring capacity in otherwise uninstrumented volcanoes, complementary to remote sensing of ground deformation. Plain Language Summary: Seismic signals emitted from volcanic regions carry invaluable information on the transport of magma or/and hydrothermal fluid beneath the volcanic edifice. During explosive eruptions, seismic signal can be detected and analyzed using regional or global seismic networks. On the other hand, during the intereruption interval, repetitive volcanoseismic signals directly linked to fluid transport in the magma plumbing system rely on in situ seismic stations near the volcano edifice. Using repetitive seismic signals from one of the most active volcanoes in Aso as an example, we demonstrate that synchronous seismic signals emitted from a shallow crack‐like conduit and a deep chamber roof can be detected at seismic stations even hundreds of kilometers away from their sources. The inclusion of data at distant stations from established global and regional seismic networks improves source characterization, expands the detection capability of repetitive volcanoseismic signals backward in time and increases the monitoring capacity of uninstrumented volcanoes. Key Points: Repetitive noneruptive volcanoseismic signals are often monitored by in situ seismic networks but rarely detected in distant stationsSeismic data at distant stations validate source properties of very‐long‐period signal and synchronous deformation events in Aso volcanoRemote monitoring using established regional seismic networks helps provide insights into in otherwise uninstrumented volcanoes [ABSTRACT FROM AUTHOR]

Objective: In recent years, natural language processing (NLP) techniques have progressed, and their application in the medical field has been tested. However, the use of NLP to detect symptoms from medical progress notes written in Japanese, remains limited. We aimed to detect 2 gastrointestinal symptoms that interfere with the continuation of chemotherapy—nausea/vomiting and diarrhea—from progress notes using NLP, and then to analyze factors affecting NLP. Materials and methods: In this study, 200 patients were randomly selected from 5277 patients who received intravenous injections of cytotoxic anticancer drugs at Kagawa University Hospital, Japan, between January 2011 and December 2018. We aimed to detect the first occurrence of nausea/vomiting (Group A) and diarrhea (Group B) using NLP. The NLP performance was evaluated by the concordance with a review of the physicians' progress notes used as the gold standard. Results: Both groups showed high concordance: 83.5% (95% confidence interval [CI] 74.1-90.1) in Group A and 97.7% (95% CI 91.3-99.9) in Group B. However, the concordance was significantly better in Group B (P =.0027). There were significantly more misdetection cases in Group A than in Group B (15.3% in Group A; 1.2% in Group B, P =.0012) due to negative findings or past history. Conclusion: We detected occurrences of nausea/vomiting and diarrhea accurately using NLP. However, there were more misdetection cases in Group A due to negative findings or past history, which may have been influenced by the physicians' more frequent documentation of nausea/vomiting. [ABSTRACT FROM AUTHOR]

Objective: This study examines the extent to which retracted articles pertaining to COVID-19 have been shared via social and mass media based on altmetric scores. Methods: Seventy-one retracted articles related to COVID-19 were identified from relevant databases, of which thirty-nine had an Altmetric Attention Score obtained using the Altmetrics Bookmarklet. Data extracted from the articles include overall attention score and demographics of sharers (e.g., geographic location, professional affiliation). Results: Retracted articles related to COVID-19 were shared tens of thousands of times to an audience of potentially hundreds of millions of readers and followers. Twitter was the largest medium for sharing these articles, and the United States was the country with the most sharers. While general members of the public were the largest proportion of sharers, researchers and professionals were not immune to sharing these articles on social media and on websites, blogs, or news media. Conclusions: These findings have potential implications for better understanding the spread of misleading or false information perpetuated in retracted scholarly publications. They emphasize the importance of quality peer review and research ethics among journals and responsibility among individuals who wish to share research findings. [ABSTRACT FROM AUTHOR]

OBJECTIVE: In recent years, natural language processing (NLP) techniques have progressed, and their application in the medical field has been tested. However, the use of NLP to detect symptoms from medical progress notes written in Japanese, remains limited. We aimed to detect 2 gastrointestinal symptoms that interfere with the continuation of chemotherapy--nausea/vomiting and diarrhea--from progress notes using NLP, and then to analyze factors affecting NLP. MATERIALS AND METHODS: In this study, 200 patients were randomly selected from 5277 patients who received intravenous injections of cytotoxic anticancer drugs at Kagawa University Hospital, Japan, between January 2011 and December 2018. We aimed to detect the first occurrence of nausea/vomiting (Group A) and diarrhea (Group B) using NLP. The NLP performance was evaluated by the concordance with a review of the physicians' progress notes used as the gold standard. RESULTS: Both groups showed high concordance: 83.5% (95% confidence interval [CI] 74.1-90.1) in Group A and 97.7% (95% CI 91.3-99.9) in Group B. However, the concordance was significantly better in Group B (P = .0027). There were significantly more misdetection cases in Group A than in Group B (15.3% in Group A; 1.2% in Group B, P = .0012) due to negative findings or past history. CONCLUSION: We detected occurrences of nausea/vomiting and diarrhea accurately using NLP. However, there were more misdetection cases in Group A due to negative findings or past history, which may have been influenced by the physicians' more frequent documentation of nausea/vomiting. [ABSTRACT FROM AUTHOR]

Continual development necessitates innovation. One must discover seeds of innovation and then concentrate resources on these seeds. To do so, one must recognize technology trends and then adopt and execute appropriate innovation strategies. This study used advanced change point detection method to investigate leading indicators that represent changes in technology trends. We examine patents, papers, and newspaper articles in Japan and US for 55 technologies. Results suggest that patents can be more appropriate as leading indicators than either papers or newspapers. This result can contribute to appropriate innovation strategies for planning and updating, and can provide tools that are useful to decision-makers. [ABSTRACT FROM AUTHOR]

After the long discussions in Japan over the introduction of a general clause on copyright exceptions since 2007, the 'flexible' provisions on copyright exceptions (Arts. 30-4, 47-4 and 47-5) were finally introduced into the Japanese Copyright Act in 2018 and came into effect in 2019. They differ widely from the US fair use clause and the UK fair dealing provisions. This article focuses on Art. 30-4, which comprehensively allows an exploitation of a work that is aimed at neither enjoying nor causing another person to enjoy the work. In particular, any exploitation for text-and-data mining (TDM) is widely permitted by any means under Art. 30-4, including for commercial purposes. The underlying theory behind this relates to the nature of copyright, or the justification for copyright protection that an exploitation not for 'enjoyment' purposes is beyond the inherent scope of copyright because it does not prejudice the opportunities of the copyright holders to receive compensation. While this might sound unusual, it is interesting to note that some similar theories can be found in Europe, some of which try to widely exclude TDM activities from the scope of copyright based on the idea of 'a use as a work'. Considering such common characteristics of the theories regarding copyright and 'enjoyment' of a work, Art. 30-4 of the Japanese Copyright Act and the theoretical justification for it might have implications for other jurisdictions regarding copyright exceptions or the substantive scope of copyright. [ABSTRACT FROM AUTHOR]

Aims: Existing analysis methods about the relationships between the long-term care (LTC) risks and determinants of the elderly often experience issues of independence, linearity and homogeneity. Such methodological issues are particularly problematic when the relationships are complicated, making the prioritization of LTC interventions to groups with different care needs difficult. To overcome these shortcomings, this study made an initial attempt to identify representative patterns of elderly people's LTC risks associated with different determinants, from a methodological perspective. Methods: A data mining approach (Exhaustive CHAID) is applied to data collected from 26 357 elderly people in a Japanese city in 2016. It can automatically segment the samples into a tree structure that accommodates nonlinear, heterogeneous and sequential relationships, without caring about issues of independence across determinants. Results: In total, 16 representative patterns are derived, among which four patterns are considerably riskier (the unhealthy percentage >10.0%), and five are moderately riskier (the unhealthy percentage is 5.0%-10.0%). Age is the most important determinant, followed by locomotor function, cognitive function, homebound, gender and residential location, in that order, which all show heterogeneous associations with the risk patterns. Conclusions: The Exhaustive CHAID is suitable to derive scientifically-sound insights into an early screening of risk factors for pre-frail groups and tailor-made preventive LTC interventions for frail groups in a flexible and objective way. Geriatr Gerontol Int 2020; 20: 674-679. [ABSTRACT FROM AUTHOR]

It has been Two years since the bill to legalize casinos in Japan was enacted. Since casinos are avoided by many people in Japan, the promoters try to keep gambling images out of their publicity as much as possible. These promoters are relatively irreverent as to the effect of their promotions in order to enter the Japanese market successfully. Therefore, in this study, the perceptive aspects of those who do not have positive thoughts about casinos have been explored. This was done by designing a hypothetical human cognitive model. Data obtained from a total of 400 subjects through questionnaire survey was analyzed. From the results, it was found that the existing conventional PR methods of promoting casinos as resorts did not necessarily reduce the resistance and aversion to casinos in the minds of their detractors. The initiatives were discussed in order to make the opposition change their minds effectively through educating them to a level of understanding of what casinos are in terms of rules etc., as well as letting them try gambling so as to measure their practical feelings. [ABSTRACT FROM AUTHOR]

Data mining extracts useful knowledge from big data. The extracted knowledge in data mining is often represented by association rules, and association rules can be also used for classification. However, when association rules for classification (called class association rules) are extracted, a large number of data with class labels are necessary, which requires a lot of cost of manual annotation. Therefore, this paper proposes a semisupervised learning method for rule extraction, where a small number of labeled data and a large number of unlabeled data are used to efficiently extract class association rules. In detail, this paper proposes two types of classifiers using class association rules: one is a classifier based on semisupervised learning, and the other is that based on both supervised and semisupervised learning. The second method builds several classifiers using supervised learning and semisupervised learning and the classification results of these classifiers are integrated to make the final decision. As an association rule mining method, Genetic Network Programming (GNP), which is one of the graph‐based evolutionary algorithms is used. GNP has shown distinguished classification ability in some applications; therefore, one of the other objectives of this paper is to extend the applicability of GNP to data mining based on semisupervised learning. In the experiments, the classification accuracy is evaluated using some benchmark datasets by comparing with some conventional methods. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In the aging society, reducing vehicle crashes caused by elderly drivers has become a crucial issue. To find effective methods to reduce these vehicle crashes, it is necessary to give some insights into the characteristics of vehicle crashes and those of traffic violations caused by elderly drivers. However, multiple significant factors associated with crossing crashes due to elderly drivers were not extensively observed in previous studies. To fill this research gap, this study identifies the crash pattern and examines the environmental, vehicle, and driver factors associated with crossing crashes due to elderly drivers. The 5-year crash data in Toyota City, Japan, are used for empirical analysis. The emerging data mining method called association rules mining is applied to discover various factors associated with crossing crashes of elderly and nonelderly drivers, respectively. The significant findings indicate that (1) elderly drivers are more likely to lead to crossing or right-turn crashes, compared with nonelderly drivers; (2) there are more factors including crash location (intersection without signal), lighting (daylight), road condition (dry and other), weather condition (clear and raining), vehicle type (light motor truck), and traffic violation (fail to confirm safety) associated with the large proportion of crossing crashes due to elderly drivers. The findings of this study can be used by traffic safety professionals to implement some countermeasures to reduce the crossing crashes due to elderly drivers. [ABSTRACT FROM AUTHOR]

Is it possible to predict location, time and magnitude of earthquakes through identifying their precursors based on remotely sensed data? Earthquakes are usually preceded by unusual natural incidents that are considered as earthquake precursors. With the recent advances in remote sensing techniques which have made it possible monitoring the earth's surface with different sensors, scientists are now able to better study earthquake precursors. Thus, the present study aims at developing the algorithm of classic PS-InSAR processing for obtaining crustal deformation values at the epicenter of earthquakes with magnitude larger than 5.0 on the Richter scale and with oblique thrust faulting and then after calculating temperature values using remotely sensed thermal imagery at the epicenter of same earthquakes; thermal and crustal deformation anomalies were calculated using data mining techniques before earthquake occurrence. In the next stage, taking the correlation between thermal anomalies and crustal deformation anomalies at the epicenter of the study earthquakes into account, an integrated technique was proposed to predict probable magnitude and time of oblique thrust earthquakes occurrence over the earthquake-prone areas. Eventually, the validity of the proposed algorithm was evaluated for an earthquake with a different focal mechanism. The analysis results of the thermal anomalies and crustal deformation anomalies at the epicenter of April 16, 2016, Japan-Kumamoto earthquake of magnitude 7.0 with strike-slip faulting, showed completely different trends than the suggested patterns by the proposed algorithm. [ABSTRACT FROM AUTHOR]

Data mining from published papers can generate large experimental datasets that have been overlooked in computational materials informatics. We developed an open web system Starrydata2 to accelerate a comprehensive digitization of data of materials from as-reported plot images in published papers, without sample selection based on performance. By plotting results obtained from our dataset on experimental thermoelectric properties of 434 samples of rock-salt-type (PbTe-type) thermoelectric materials, we revealed differences in electronic structure of parent compounds PbTe, PbSe, PbS, and SnTe from just experimental data. We observed that the calculated Seebeck coefficients were fairly consistent with experimental data for n-type PbTe but not for p-type PbTe, indicating possible modifications in its valence-band electronic structure. We evaluated the electron relaxation time τel from 207 reported samples of n-type PbTe by combining calculations and experimental data. We found that τel is not a constant but varies by at least two orders of magnitude. Achieving long τel was suggested to be critical in increasing the thermoelectric figure of merit ZT. Reproduced with permission from Thermoelectrics Society of Japan. [ABSTRACT FROM AUTHOR]

What is known and objective: Haematological toxicities such as neutropaenia are a common side effect of ganciclovir (GCV); however, risk factors for GCV‐induced neutropaenia have not been well established. Decision tree (DT) analysis is a typical technique of data mining consisting of a flow chart–like framework that shows various outcomes from a series of decisions. By following the flow chart, users can estimate combinations of risk factors that may increase the probability of certain events. In our previous study, we demonstrated the usefulness of this approach in the evaluation of adverse drug reactions. Therefore, we aimed to construct a risk prediction model of GCV‐induced neutropaenia including severity grade. Methods: We performed a retrospective study at the Hokkaido University Hospital and enrolled patients who received GCV between April 2008 and March 2018. Neutropaenia was defined as an absolute neutrophil count (ANC) <1500 cells/mm3 and a decrease to <75% relative to baseline. We classified the patients who developed neutropaenia in three groups (Grades 2‐4) based on the National Cancer Institute‐Common Terminology Criteria for Adverse Events. Data collection was achieved through the retrieval of medical records. We employed a chi‐squared automatic interaction detection algorithm to construct the DT model and compared the accuracies to the logistic regression model (a conventional statistical method) to evaluate the established model. Results and discussion: In total, 396 adult patients were included in the study; 61 (15.4%) developed neutropaenia. Three predictive factors (hematopoietic stem cell transplantation, baseline ANC <3854 cells/mm3 and duration of therapy ≥15 days) were extracted using the DT analysis to produce five subgroups, the incidence of neutropaenia ranged between 1.7% and 52.8%. In each subgroup, patients who developed neutropaenia were categorized based on the severity. The accuracies of each model were the same (84.6%), which indicated precision. What is new and conclusion: We successfully built a risk prediction model of GCV‐induced neutropaenia including severity grade. This model is expected to assist decision‐making in the clinical setting. [ABSTRACT FROM AUTHOR]

In Japan, the Act on the Promotional Development of Areas for Specified Integrated Resort Facilities (IR bill) was enacted in 2018. Japanese gambling industries based around bicycle racing, horse racing, auto racing, and powerboat racing are already in operation. However, many citizens are currently opposed to the introduction of casinos. Therefore, we explored the kinds of casino design concepts that could be acceptable in modern Japanese society. In this research, data relating to both casino-related knowledge and experience were collected via questionnaires. All data used in this study were obtained from Japanese adults who have knowledge of and experience with gambling. According to our results, "location" was the leading factor in determining the viability of a potential casino. Additionally, we discuss other important aspects of casino design. [ABSTRACT FROM AUTHOR]

Anti-vaccination sentiment exists worldwide and Japan is no exception. Health professionals publish pro-influenza vaccination messages online to encourage proactive seeking of influenza vaccination. However, influenza vaccine coverage among the Japanese population is less than optimal. The contents of pro- and anti-influenza vaccination websites may contribute to readers' acceptance of one or the other position. We aimed to use a text-mining method to examine frequently appearing content on websites for and against influenza vaccination. We conducted online searches in January 2017 using two major Japanese search engines (Google Japan and Yahoo! Japan). Targeted websites were classified as 'pro', 'anti' or 'neutral' depending on their claims, with author(s) classified as 'health professionals', 'mass media' or 'laypersons'. Text-mining analysis was conducted, and statistical analysis was performed using a chi-squared test. Of the 334 websites analyzed, 13 content topics were identified. The three most frequently appearing content topics on pro-vaccination websites were vaccination effect for preventing serious cases of influenza, side effects of vaccination, and efficacy rate of vaccination. The three most frequent topics on anti-vaccination websites were ineffectiveness of influenza vaccination, toxicity of vaccination, and side effects of vaccination. The main disseminators of each topic, by author classification, were also revealed. We discuss possible tactics of online influenza vaccination promotion to counter anti-vaccination websites. [ABSTRACT FROM AUTHOR]

Objectives. Traditional Japanese Kampo medicines have been integrated into the Japanese national health-care system. In Japan, the Ministry of Health, Labor, and Welfare's website discloses adverse drug-event data that have been obtained from medical personnel reports investigated by the Pharmaceutical and Medical Devices Agency. Using these data, we investigated adverse events associated with ethical Kampo formulations. Methods. Reports of adverse events associated with ethical Kampo formulations from the domestic adverse-event data were obtained from July 30, 2003, to March 31, 2018. Adverse events were then categorized, and the relationships between categories of adverse events and crude drugs were analyzed. Results. There were 4,232 reported adverse events associated with ethical Kampo formulations. The numbers of events by category were as follows: events related to liver injury, 1,193; lung injury, 1,177; pseudoaldosteronism, 889; mesenteric phlebosclerosis, 223; drug eruption, 185; and others, 565. Among events related to both liver injury and lung injury, approximately 70% were suspected to be induced by Kampo formulations containing Scutellariae Radix. The pseudoaldosteronism-related events, which are induced by Glycyrrhizae Radix, included several events related to muscle injury, heart failure, and arrhythmia. Events related to mesenteric phlebosclerosis, believed to be induced by long-term use of Kampo formulas containing Gardeniae Fructus, increased remarkably during the study period. Among the events related to drug eruption, approximately 35% were suspected to be induced by Kampo formulations containing Ephedrae Herba. Conclusion. Kampo medicines may cause various adverse events. The present results provide valuable information regarding adverse events associated with Kampo medicines from the viewpoint of patient safety. [ABSTRACT FROM AUTHOR]

Aim: The consideration of patients' needs in terms of research outcomes is emphasized in research promotion to eradicate hepatitis B virus according to the Basic Act on Hepatitis Measures in Japan. This study analyzed patients' attitudes toward experienced antiviral therapies for chronic hepatitis B and their need for future therapies. Methods: A self‐administered questionnaire comprising 124 questions was completed among patients with chronic hepatitis B from 61 core‐center hospitals designated to implement and research policies on hepatitis in 47 prefectures from August 2013 to January 2014 (n = 3021, response rate = 51%). Results: In decision‐tree models with 333 variables generated from the questionnaire data, patients' satisfaction with therapy and reduction in anxiety about therapy were dependent on favorable therapeutic effects, sufficient information provided by the physician, and fewer lifestyle disturbances. Medical expenses were not selected at a superior branch because subsidy for antiviral therapy started in 2010. In correspondence analysis of free text answers, patients' need for therapy and support mechanisms differed among their attributes, including a great need for novel therapy in older men, hope for avoidance of lifestyle disturbance in younger men, and alleviation of painful experience with the disease in women. Conclusions: Continual provision of sufficient information is necessary to improve the utility of antiviral therapy for chronic hepatitis B as well as for favorable therapeutic effects. The patients believed that novel drugs and support would reduce the diverse burden of the disease on their lives. [ABSTRACT FROM AUTHOR]

UNESCO defines Education for Sustainable Development (ESD) as a means of addressing present and future worldwide challenges by creating sustainable and resilient societies. ESD content and approaches have been applied throughout the tertiary curriculum, but one area that lags is English as a Foreign Language (EFL), even though environmental themes and topics--such as global warming--are commonly used. Although these topics are useful for raising student awareness of critical issues, lessons dedicated to these topics often fail to engage students beyond the purposes of English-language teaching. This represents a missed opportunity in countries like Japan, where students in higher education have limited exposure to environmental topics. This research examines the role that environmental topics play in EFL textbooks through an analysis of a corpus of more than 55,000 words garnered from EFL textbooks commonly used in Japanese higher education. The research aims to discover themes and patterns found in the corpus by the novel application of text analysis, data mining techniques, and corpus analysis tools. The author proposes a framework to support and improve EFL lessons that integrate environmental content with the ultimate aim of strengthening ESD mainstreaming. [ABSTRACT FROM AUTHOR]

In addition to offshore fishing, high sea fishing has become another important supply channel for seafood. The pelagic catches of China, Japan, and Korea (CJK) account for 60% of the global total, and an analysis of their activities adds essential clarity regarding global fishery resources. This paper develops a framework for analyzing the activities of HSF vessels based on satellite AIS data from 2019, which is used to study the spatial-temporal characteristics of the lengths, speeds, trajectories, and trajectory densities of HSF vessels, the numbers of active vessels, and their average fishing times. The analysis results show that: 1) Chinese HSF vessels are mostly small, relative to Japanese and Korean ships; 2) The speed of Japanese HSF vessels is consistently the highest; 3) All HSF vessels mainly fish in the Northwest Pacific, Western Central Pacific, Eastern Central Pacific, Southeast Pacific, Eastern Central Atlantic, Southeast Atlantic, and Western Indian Oceans; 4) The trajectory distribution of Chinese and Japanese vessels are similar, and both are more widely distributed than Korean vessels; 5) Chinese and Korean HSF vessels mostly enter the Atlantic through the Drake Passage, while Japanese ships mostly enter through the Panama Canal; 6) Chinese HSF vessels fish in Antarctic fisheries all year, while Korean ships aim to fish in Antarctic fisheries in the Spring, Summer, and Winter; 7) China has the largest number of HSF vessels in all fisheries, but their average fishing time is the shortest; 8) The average fishing time of all HSF vessels in Spring and Summer is short, increases during the Autumn, and continues to rise in some fisheries during Winter. This study is not only of great significance for the management and conservation of marine resources, but is also a valuable reference for the promotion of international cooperation in safeguarding marine fisheries. [ABSTRACT FROM AUTHOR]

The development of new anti-HIV drugs and advances in antiretroviral therapy (ART) regimens have enabled longer and more effective treatments in people living with HIV (PLWH). However, the aging of PLWHs is another issue that needs to be addressed. In addition to ART, many PLWHs frequently receive medications for various comorbidities. However, real-world data on the occurrence of adverse events in PLWHs and their causative drugs are rare. Therefore, this study aimed to clarify the characteristics of adverse event reports among PLWHs in Japan. PLWH cases with adverse events were comprehensively searched and analyzed using the Japanese Adverse Drug Event Report database (JADER). Despite changes in guideline-recommended ART regimens, anti-HIV drugs were the main cause of adverse events in PLWHs throughout the study period. However, considerable variations have been observed in the reporting rate of anti-HIV drug classes registered as causative drugs in JADER, especially for anchor drugs. In other words, the reporting rate of integrase strand transfer inhibitors has increased in recent years, while that of protease inhibitors and non-nucleoside reverse transcriptase inhibitors has decreased. Immune reconstitution inflammatory syndrome was the most reported adverse event and was frequently noticed by healthcare providers managing patients with HIV infections. The trends in adverse event reports for female and older patients differed from those for the overall population. This study may provide insights that can help in the establishment of optimal management strategies for PLWHs.

Occupants’ behavior and their interaction with home appliances are crucial for assessing building energy consumption. This study proposes a new methodology for monitoring the energy consumed in building end-use loads to build an advisory system. The built system alerts occupants to take certain measures (prioritized recommendations) to reduce energy consumption of end-use loads. The quantification of potential savings is also provided upon following said measures. The proposed methodology is also capable of evaluating the energy savings performed by the occupants. The system works based on the analysis of historical data generated by occupants using data mining techniques to output highly feasible recommendations. For demonstration purposes, the methodology was tested on the real dataset of a building in Japan. The dataset includes detailed energy consumption of end-use loads, categorized as hot water supply, lighting, kitchen, refrigerator, entertainment & information, housework & sanitary, and others. Results suggest that the developed models are accurate, and that it is possible to save up to 21% of total energy consumption by only changing occupants’ energy use habits. [ABSTRACT FROM AUTHOR]

Objective: In Japan, the human papillomavirus (HPV) vaccination rate has sharply fallen to nearly 0% due to sensational media reports of adverse events. Online anti-HPV-vaccination activists often warn readers of the vaccine's dangers. Here, we aimed to examine frequently appearing contents on pro- and anti-HPV vaccination websites.Methods: We conducted online searches via two major search engines (Google Japan and Yahoo! Japan). Targeted websites were classified as "pro," "anti," or "neutral" according to their claims, with the author(s) classified as "health professionals," "mass media," or "laypersons." We then conducted a text mining analysis.Results: Of the 270 sites analyzed, 16 contents were identified. The most frequently appearing contents on pro websites were vaccine side effects, preventable effect of vaccination, and cause of cervical cancer. The most frequently appearing contents on anti websites were vaccine side effects, vaccine toxicity, and girls who suffer from vaccine side effects. Main disseminators of each content according to the author's expertise were also revealed.Conclusion: Pro-HPV vaccination websites should supplement deficient contents and respond to frequent contents on anti-HPV websites.Practice Implications: Effective tactics are needed to better communicate susceptibility to cervical cancer, frequency of side effects, and responses to vaccine toxicity and conspiracy theories. [ABSTRACT FROM AUTHOR]

The increasing power of technology puts new, advanced statistical tools at the disposal of researchers. This is one of the first research articles to use a data mining tool—namely, decision trees—to analyze the behavior of inbound tourists for the purpose of effective future destination marketing in Japan. The research results of approximately 4,000 observations show that the main motivation for visitors’ future return is not driven by experiences had during their most current visit but rather by experiences anticipated in the future, such as visiting hot springs or immersing themselves in beautiful natural settings. The data mining method largely excludes the possibility of the intrusion of researcher subjectivity and is conducive to useful discoveries of certain visitor patterns in large data sets, providing governments and destination marketing organizations with additional tools to better formulate effective destination marketing strategies. [ABSTRACT FROM AUTHOR]

Objectives Several publications concerning decision tree (DT) analysis in medical fields have recently demonstrated its usefulness for defining prognostic factors in various diseases. However, there are minimal reports on the predictors of adverse drug reactions. We attempted to use DT analysis to discover combinations of multiple risk factors that would increase the risk of nephrotoxicity associated with vancomycin (VCM). To demonstrate the usefulness of DT analysis, we compared its predictive performance with that of multiple logistic regression analysis. Method A single-centre, retrospective study was conducted at Hokkaido University Hospital. A total of 592 patients, who received intravenous administrations of VCM between November 2011 and April 2016, were enrolled. Nephrotoxicity was defined as an increase in serum creatinine of ≥0.5 mg/dL or a ≥50% increase in serum creatinine from the baseline. Risk factors for VCM nephrotoxicity were extracted from previous reports. In the DT analysis, a chi-squared automatic interaction detection algorithm was constructed. For evaluating the established algorithms, a 10-fold cross validation method was adopted to calculate the misclassification risk of the model. Moreover, to compare the accuracy of the DT analysis, multiple logistic regression analysis was conducted. Results Eighty-seven (14.7%) patients developed nephrotoxicity. A VCM trough concentration of ≥15.0 mg/L, concomitant medication (vasopressor drugs and furosemide), and a duration of therapy ≥14 days were extracted to build the DT model, in which the patients were divided into 6 subgroups based on variable rates of nephrotoxicity, ranging from 4.6 to 69.6%. The predictive accuracies of the DT and logistic regression models were similar (87.3%, respectively), indicating that they were accurate. Conclusion This study suggests the usefulness of DT models for the evaluation of adverse drug reactions. [ABSTRACT FROM AUTHOR]

Using two household surveys, this paper investigates whether the saving rates of richer households are higher than those of poorer households in Japan. We construct a number of proxies for lifetime wealth, including those original to this study, and find marginally positive correlations between saving rates and lifetime wealth for working age households. We further find that the relationship between saving rates and lifetime wealth differs depending on the life stage of individual households. Older households with higher lifetime wealth appear to be dissaving to some extent, which is more or less consistent with the lifecycle model of consumption. [ABSTRACT FROM AUTHOR]

Teeth are known to be the most accurate age indicators of human body and are frequently applied in forensic age estimation. We aimed to validate data mining-based dental age estimation, by comparing the accuracy of the estimation and classification performance of 18-year thresholds with conventional methods and with data mining-based age estimation. A total of 2657 panoramic radiographs were collected from Koreans and Japanese populations aged 15 to 23 years. They were subdivided into a training and internal test set of 900 radiographs each from Koreans, and an external test set of 857 radiographs from Japanese. We compared the accuracy and classification performance of the test sets from conventional methods with those from the data mining models. The accuracy of the conventional method with the internal test set was slightly higher than that of the data mining models, with a slight difference (mean absolute error < 0.21 years, root mean square error < 0.24 years). The classification performance of the 18-year threshold was also similar between the conventional method and the data mining models. Thus, conventional methods can be replaced by data mining models in forensic age estimation using second and third molar maturity of Korean juveniles and young adults., (© 2023. The Author(s).)

Objective: To identify the trends in tolvaptan prescription and the association between aging and tolvaptan-induced hypernatremia., Materials and Methods: A health insurance claims database and a spontaneous adverse drug reaction database were used., Results: Of all patients who had been prescribed tolvaptan, the proportion of patients aged 60 - 79 years and ≥ 80 years was consistent at ~ 40%. Moreover, the prescription frequency of tolvaptan increased over time for patients in the same age groups. The adjusted reporting odds ratio of tolvaptan-induced hypernatremia was 5.54 (95% confidence interval, 3.31 - 9.25) in patients aged ≥ 60 years from among all patients and 2.09 (95% confidence interval, 1.59 - 2.75) in those aged ≥ 80 years from among those aged ≥ 60 years., Conclusion: It may be necessary to be aware of hypernatremia in elderly patients who are expected to have increased prescriptions of tolvaptan.

Background Elucidating public concerns regarding vaccinations is important for successful immunization programs. The objective of the present study was to categorize public concerns regarding influenza vaccinations in Japan by analyzing a massive web-based question dataset. Methods The Yahoo! Chiebukuro (Japanese Yahoo! Answers) Dataset, which includes more than 16 million questions collected between April 2004 and April 2009, was used in this study. We sequentially filtered data to obtain questions on influenza vaccinations. Any questions that met our exclusion criteria concerning veterinary vaccines or computer virus vaccines were removed from the analysis. Filtered questions and their answers were manually analyzed for their content by a team of board-certified pediatricians. Results After filtering data, we obtained 1950 questions regarding influenza vaccinations. The three most frequently asked questions were regarding the vaccination schedule, safety, and effectiveness. When we analyzed monthly trends in question contents, we noted the emergence of similar questions in the same period every year. Therefore, we classified the time periods of each year into three parts: (1) from April to the commencement of seasonal influenza vaccinations (September), (2) from October until the epidemic period, and (3) the epidemic period. Two interesting results were obtained: concerns regarding effectiveness abruptly increased during the epidemic period, and pregnant or breastfeeding women increasingly asked questions regarding feasibility between October and the epidemic period. Conclusions The questions and concerns collected and analyzed in this study illustrate that the public have questions about the influenza vaccine and also that questions changed with periodical consistency. These results highlight the possible usefulness of providing the public with the latest and correct information to their questions in a timely manner, for example via an official health website. [ABSTRACT FROM AUTHOR]