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Background: Standardized coding of plays an important role in radiology reports' secondary use such as data analytics, data-driven decision support, and personalized medicine. RadLex, a standard radiological lexicon, can reduce subjective variability and improve clarity in radiology reports. RadLex coding of radiology reports is widely used in many countries, but translation and localization of RadLex in China are far from being established. Although automatic RadLex coding is a common way for non-standard radiology reports, the high-accuracy cross-language RadLex coding is hardly achieved due to the limitation of up-to-date auto-translation and text similarity algorithms and still requires further research.Methods: We present an effective approach that combines a hybrid translation and a Multilayer Perceptron weighting text similarity ensemble algorithm for automatic RadLex coding of Chinese structured radiology reports. Firstly, a hybrid way to integrate Google neural machine translation and dictionary translation helps to optimize the translation of Chinese radiology phrases to English. The dictionary is made up of 21,863 Chinese-English radiological term pairs extracted from several free medical dictionaries. Secondly, four typical text similarity algorithms are introduced, which are Levenshtein distance, Jaccard similarity coefficient, Word2vec Continuous bag-of-words model, and WordNet Wup similarity algorithms. Lastly, the Multilayer Perceptron model has been used to synthesize the contextual, lexical, character and syntactical information of four text similarity algorithms to promote precision, in which four similarity scores of two terms are taken as input and the output presents whether the two terms are synonyms.Results: The results show the effectiveness of the approach with an F1-score of 90.15%, a precision of 91.78% and a recall of 88.59%. The hybrid translation algorithm has no negative effect on the final coding, F1-score has increased by 21.44% and 8.12% compared with the GNMT algorithm and dictionary translation. Compared with the single similarity, the result of the MLP weighting similarity algorithm is satisfactory that has a 4.48% increase compared with the best single similarity algorithm, WordNet Wup.Conclusions: The paper proposed an innovative automatic cross-language RadLex coding approach to solve the standardization of Chinese structured radiology reports, that can be taken as a reference to automatic cross-language coding. [ABSTRACT FROM AUTHOR]

Background: Multifunction surveillance alerting systems have been found to be beneficial for the operating room and labor and delivery. This paper describes a similar system developed for in-hospital acute care environments, AlertWatch Acute Care (AWAC). Results: A decision support surveillance system has been developed which extracts comprehensive electronic health record (EHR) data including live data from physiologic monitors and ventilators and incorporates them into an integrated organ icon-based patient display. Live data retrieved from the hospitals network are processed by presenting scrolling median values to reduce artifacts. A total of 48 possible alerts are generated covering a broad range of critical patient care concerns. Notification is achieved by paging or texting the appropriated member of the critical care team. Alerts range from simple out of range values to more complex programing of impending Ventilator Associated Events, SOFA, qSOFA, SIRS scores and process of care reminders for the management of glucose and sepsis. As with similar systems developed for the operating room and labor and delivery, there are green, yellow, and red configurable ranges for all parameters. A census view allows surveillance of an entire unit with flashing or text to voice alerting and enables detailed information by windowing into an individual patient view including live physiologic waveforms. The system runs via web interface on desktop as well as mobile devices, with iOS native app available, for ease of communication from any location. The goal is to improve safety and adherence to standard management protocols. Conclusions: AWAC is designed to provide a high level surveillance view for multi-bed hospital units with varying acuity from standard floor patients to complex ICU care. Alerts are generated by algorithms running in the background and automatically notify the selected member of the patients care team. Its value has been demonstrated for low acuity patients, further study is required to determine its effectiveness in high acuity patients. [ABSTRACT FROM AUTHOR]

Background: Cervical cancer is the fourth most common cancer worldwide. Organized screening has achieved significant reductions in cervical cancer incidence and mortality in many high-income countries (HICs). But the gap between HICs and low-and-middle-income countries (LMICs) is still substantial as the highest burden of the disease is in LMICs. Cameroon is a LMIC, where cervical cancer is the leading cause of cancer-related deaths among women, only 3–5% of eligible women have been screened and there is no effective national cervical cancer prevention program. Objective(s): Identify facilitators and barriers to the implementation and uptake of existing cervical cancer screening programs in Cameroon to inform the implementation of a comprehensive national program. Methods: We conducted a scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews (PRISMA-ScR). Google Scholar and five electronic databases (PubMed, CINAHL, Embase, Cochrane library and Web of Science) were searched systematically from 2012 to 2022. Articles on cervical cancer screening programs in Cameroon were eligible for inclusion. Two reviewers independently screened search results and extracted relevant data. Results: A total of 182 articles were identified using our search strategy, and 20 were included. There was scarcity of publications from the North, Adamawa, East and South regions of Cameroon. Barriers and facilitators found were presented using the World Health Organisation framework for health systems. Cross-cutting barriers were: (1) the lack of a national training curriculum for screening providers with no elaborate, harmonized screening and treatment algorithm for cervical precancers; and (2) women's lack of information about cervical cancer screening activities. Conversely, provision of screening services at a low or no cost to women in some programs and the feasibility of using novel point of care screening methods like the Human Papillomavirus DNA test were identified as facilitators. Conclusion: This scoping review indicates that there are knowledge and research gaps concerning the state of cervical cancer screening services in some regions of Cameroon. Moreover, it underlines the need for comprehensive cancer control policies and practices integrating all six-health system building blocks to reduce disparities between regions, and rural versus urban areas in Cameroon. [ABSTRACT FROM AUTHOR]

Background: The patient-oriented and need-based care of multi-morbid patients with healthcare services and assistive products can be a highly complex task for the general practitioners (GPs). An algorithm-based digital recommendation system (DRS) for healthcare services was developed within the context of the telemedicine research project ATMoSPHÄRE. The plausibility of the DRS was tested and the results used to examine if, and to what degree, the DRS provides useful assistance to GPs. Methods: The plausibility of the recommendations of the DRS were tested with the Delphi procedure (n = 8) and Interviews (n = 4) in collaboration with the GPs. They proposed services and assistive products they considered appropriate for two multi-morbid patients. Furthermore, GPs had to report whether, and to what degree they deemed the algorithm-generated recommendations appropriate. Significant quantitative differences between the GPs', and the algorithm-generated, recommendations were evaluated with paired-samples-Wilcoxon-test. Results: The first Delphi round revealed a high variability regarding the amount and character of services recommended by the physicians (1 to 10 recommendations, mean = 5.6, sd = 2.8). These professional recommendations converged after consideration of the algorithm-generated recommendations. The number of algorithm-generated recommendations which were judged as appropriate ranged between 7 and 17 of a total of 20 (mean = 11.9, sd = 2.5). The interviews revealed that the additional algorithm-generated recommendations which were judged appropriate contained mainly social care services. Conlusion: The DRS provides GPs with additional appropriate recommendations for the need-based care of patients, which may not have been previously considered. It can therefore be assessed as a helpful complement in the primary care of multi-morbid patients. [ABSTRACT FROM AUTHOR]