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BackgroundChatbots are applications that can conduct natural language conversations with users. In the medical field, chatbots have been developed and used to serve different purposes. They provide patients with timely information that can be critical in some scenarios, such as access to mental health resources. Since the development of the first chatbot, ELIZA, in the late 1960s, much effort has followed to produce chatbots for various health purposes developed in different ways. ObjectiveThis study aimed to explore the technical aspects and development methodologies associated with chatbots used in the medical field to explain the best methods of development and support chatbot development researchers on their future work. MethodsWe searched for relevant articles in 8 literature databases (IEEE, ACM, Springer, ScienceDirect, Embase, MEDLINE, PsycINFO, and Google Scholar). We also performed forward and backward reference checking of the selected articles. Study selection was performed by one reviewer, and 50% of the selected studies were randomly checked by a second reviewer. A narrative approach was used for result synthesis. Chatbots were classified based on the different technical aspects of their development. The main chatbot components were identified in addition to the different techniques for implementing each module. ResultsThe original search returned 2481 publications, of which we identified 45 studies that matched our inclusion and exclusion criteria. The most common language of communication between users and chatbots was English (n=23). We identified 4 main modules: text understanding module, dialog management module, database layer, and text generation module. The most common technique for developing text understanding and dialogue management is the pattern matching method (n=18 and n=25, respectively). The most common text generation is fixed output (n=36). Very few studies relied on generating original output. Most studies kept a medical knowledge base to be used by the chatbot for different purposes throughout the conversations. A few studies kept conversation scripts and collected user data and previous conversations. ConclusionsMany chatbots have been developed for medical use, at an increasing rate. There is a recent, apparent shift in adopting machine learning–based approaches for developing chatbot systems. Further research can be conducted to link clinical outcomes to different chatbot development techniques and technical characteristics.

BackgroundIn December 2019, COVID-19 broke out in Wuhan, China, leading to national and international disruptions in health care, business, education, transportation, and nearly every aspect of our daily lives. Artificial intelligence (AI) has been leveraged amid the COVID-19 pandemic; however, little is known about its use for supporting public health efforts. ObjectiveThis scoping review aims to explore how AI technology is being used during the COVID-19 pandemic, as reported in the literature. Thus, it is the first review that describes and summarizes features of the identified AI techniques and data sets used for their development and validation. MethodsA scoping review was conducted following the guidelines of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). We searched the most commonly used electronic databases (eg, MEDLINE, EMBASE, and PsycInfo) between April 10 and 12, 2020. These terms were selected based on the target intervention (ie, AI) and the target disease (ie, COVID-19). Two reviewers independently conducted study selection and data extraction. A narrative approach was used to synthesize the extracted data. ResultsWe considered 82 studies out of the 435 retrieved studies. The most common use of AI was diagnosing COVID-19 cases based on various indicators. AI was also employed in drug and vaccine discovery or repurposing and for assessing their safety. Further, the included studies used AI for forecasting the epidemic development of COVID-19 and predicting its potential hosts and reservoirs. Researchers used AI for patient outcome–related tasks such as assessing the severity of COVID-19, predicting mortality risk, its associated factors, and the length of hospital stay. AI was used for infodemiology to raise awareness to use water, sanitation, and hygiene. The most prominent AI technique used was convolutional neural network, followed by support vector machine. ConclusionsThe included studies showed that AI has the potential to fight against COVID-19. However, many of the proposed methods are not yet clinically accepted. Thus, the most rewarding research will be on methods promising value beyond COVID-19. More efforts are needed for developing standardized reporting protocols or guidelines for studies on AI.

BackgroundIn England, almost all general practices (GPs) have implemented GP online services such as electronic personal health records (ePHRs) that allow people to schedule appointments, request repeat prescriptions, and access parts of their medical records. The overall adoption rate of GP online services has been low, reaching just 28% in October 2019. In a previous study, Abd-Alrazaq et al adopted a model to assess the factors that influence patients’ use of GP online services in England. According to the previous literature, the predictive power of the Abd-Alrazaq model could be improved by proposing new associations between the existing variables in the model. ObjectiveThis study aims to improve the predictive power of the Abd-Alrazaq model by proposing new relationships between the existing variables in the model. MethodsThe Abd-Alrazaq model was amended by proposing new direct, mediating, moderating, and moderated mediating effects. The amended model was examined using data from a previous study, which were collected by a cross-sectional survey of a convenience sample of 4 GPs in West Yorkshire, England. Structural equation modeling was used to examine the theoretical model and hypotheses. ResultsThe new model accounted for 53% of the variance in performance expectancy (PE), 76% of the variance in behavioral intention (BI), and 49% of the variance in use behavior (UB). In addition to the significant associations found in the previous study, this study found that social influence (SI) and facilitating conditions (FCs) are associated with PE directly and BI indirectly through PE. The association between BI and UB was stronger for younger women with higher levels of education, income, and internet access. The indirect effects of effort expectancy (EE), perceived privacy and security (PPS), and SI on BI were statistically stronger for women without internet access, patients with internet access, and patients without internet access, respectively. The indirect effect of PPS on BI was stronger for patients with college education or diploma than for those with secondary school education and lower, whereas the indirect effect of EE on BI was stronger for patients with secondary school education or lower than for those with college education or a diploma. ConclusionsThe predictive power of the Abd-Alrazaq model improved by virtue of new significant associations that were not examined before in the context of ePHRs. Further studies are required to validate the new model in different contexts and to improve its predictive power by proposing new variables. The influential factors found in this study should be considered to improve patients’ use of ePHRs.

BackgroundThe global shortage of mental health workers has prompted the utilization of technological advancements, such as chatbots, to meet the needs of people with mental health conditions. Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual language. While numerous studies have assessed the effectiveness and safety of using chatbots in mental health, no reviews have pooled the results of those studies. ObjectiveThis study aimed to assess the effectiveness and safety of using chatbots to improve mental health through summarizing and pooling the results of previous studies. MethodsA systematic review was carried out to achieve this objective. The search sources were 7 bibliographic databases (eg, MEDLINE, EMBASE, PsycINFO), the search engine “Google Scholar,” and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently selected the studies, extracted data from the included studies, and assessed the risk of bias. Data extracted from studies were synthesized using narrative and statistical methods, as appropriate. ResultsOf 1048 citations retrieved, we identified 12 studies examining the effect of using chatbots on 8 outcomes. Weak evidence demonstrated that chatbots were effective in improving depression, distress, stress, and acrophobia. In contrast, according to similar evidence, there was no statistically significant effect of using chatbots on subjective psychological wellbeing. Results were conflicting regarding the effect of chatbots on the severity of anxiety and positive and negative affect. Only two studies assessed the safety of chatbots and concluded that they are safe in mental health, as no adverse events or harms were reported. ConclusionsChatbots have the potential to improve mental health. However, the evidence in this review was not sufficient to definitely conclude this due to lack of evidence that their effect is clinically important, a lack of studies assessing each outcome, high risk of bias in those studies, and conflicting results for some outcomes. Further studies are required to draw solid conclusions about the effectiveness and safety of chatbots. Trial RegistrationPROSPERO International Prospective Register of Systematic Reviews CRD42019141219; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019141219

BackgroundDialog agents (chatbots) have a long history of application in health care, where they have been used for tasks such as supporting patient self-management and providing counseling. Their use is expected to grow with increasing demands on health systems and improving artificial intelligence (AI) capability. Approaches to the evaluation of health care chatbots, however, appear to be diverse and haphazard, resulting in a potential barrier to the advancement of the field. ObjectiveThis study aims to identify the technical (nonclinical) metrics used by previous studies to evaluate health care chatbots. MethodsStudies were identified by searching 7 bibliographic databases (eg, MEDLINE and PsycINFO) in addition to conducting backward and forward reference list checking of the included studies and relevant reviews. The studies were independently selected by two reviewers who then extracted data from the included studies. Extracted data were synthesized narratively by grouping the identified metrics into categories based on the aspect of chatbots that the metrics evaluated. ResultsOf the 1498 citations retrieved, 65 studies were included in this review. Chatbots were evaluated using 27 technical metrics, which were related to chatbots as a whole (eg, usability, classifier performance, speed), response generation (eg, comprehensibility, realism, repetitiveness), response understanding (eg, chatbot understanding as assessed by users, word error rate, concept error rate), and esthetics (eg, appearance of the virtual agent, background color, and content). ConclusionsThe technical metrics of health chatbot studies were diverse, with survey designs and global usability metrics dominating. The lack of standardization and paucity of objective measures make it difficult to compare the performance of health chatbots and could inhibit advancement of the field. We suggest that researchers more frequently include metrics computed from conversation logs. In addition, we recommend the development of a framework of technical metrics with recommendations for specific circumstances for their inclusion in chatbot studies.

BackgroundThe recent coronavirus disease (COVID-19) pandemic is taking a toll on the world’s health care infrastructure as well as the social, economic, and psychological well-being of humanity. Individuals, organizations, and governments are using social media to communicate with each other on a number of issues relating to the COVID-19 pandemic. Not much is known about the topics being shared on social media platforms relating to COVID-19. Analyzing such information can help policy makers and health care organizations assess the needs of their stakeholders and address them appropriately. ObjectiveThis study aims to identify the main topics posted by Twitter users related to the COVID-19 pandemic. MethodsLeveraging a set of tools (Twitter’s search application programming interface (API), Tweepy Python library, and PostgreSQL database) and using a set of predefined search terms (“corona,” “2019-nCov,” and “COVID-19”), we extracted the text and metadata (number of likes and retweets, and user profile information including the number of followers) of public English language tweets from February 2, 2020, to March 15, 2020. We analyzed the collected tweets using word frequencies of single (unigrams) and double words (bigrams). We leveraged latent Dirichlet allocation for topic modeling to identify topics discussed in the tweets. We also performed sentiment analysis and extracted the mean number of retweets, likes, and followers for each topic and calculated the interaction rate per topic. ResultsOut of approximately 2.8 million tweets included, 167,073 unique tweets from 160,829 unique users met the inclusion criteria. Our analysis identified 12 topics, which were grouped into four main themes: origin of the virus; its sources; its impact on people, countries, and the economy; and ways of mitigating the risk of infection. The mean sentiment was positive for 10 topics and negative for 2 topics (deaths caused by COVID-19 and increased racism). The mean for tweet topics of account followers ranged from 2722 (increased racism) to 13,413 (economic losses). The highest mean of likes for the tweets was 15.4 (economic loss), while the lowest was 3.94 (travel bans and warnings). ConclusionsPublic health crisis response activities on the ground and online are becoming increasingly simultaneous and intertwined. Social media provides an opportunity to directly communicate health information to the public. Health systems should work on building national and international disease detection and surveillance systems through monitoring social media. There is also a need for a more proactive and agile public health presence on social media to combat the spread of fake news.

Background: The current crisis created by the coronavirus pandemic is impacting all facets of life. Coronavirus vaccines have been developed to prevent coronavirus infection and fight the pandemic. Since vaccines might be the only way to prevent and stop the spread of coronavirus. The World Health Organization (WHO) has already approved several vaccines, and many countries have started vaccinating people. Misperceptions about vaccines persist despite the evidence of vaccine safety and efficacy. Objectives: To explore the scientific literature and find the determinants for worldwide COVID-19 vaccine hesitancy as reported in the literature. Methods: PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines were followed to conduct a scoping review of literature on COVID-19 vaccine hesitancy and willingness to vaccinate. Several databases (e.g., MEDLINE, EMBASE, and Google Scholar) were searched to find relevant articles. Intervention- (i.e., COVID-19 vaccine) and outcome- (i.e., hesitancy) related terms were used to search in these databases. The search was conducted on 22 February 2021. Both forward and backward reference lists were checked to find further studies. Three reviewers worked independently to select articles and extract data from selected literature. Studies that used a quantitative survey to measure COVID-19 vaccine hesitancy and acceptance were included in this review. The extracted data were synthesized following the narrative approach and results were represented graphically with appropriate figures and tables. Results: 82 studies were included in this scoping review of 882 identified from our search. Sometimes, several studies had been performed in the same country, and it was observed that vaccine hesitancy was high earlier and decreased over time with the hope of vaccine efficacy. People in different countries had varying percentages of vaccine uptake (28–86.1%), vaccine hesitancy (10–57.8%), vaccine refusal (0–24%). The most common determinants affecting vaccination intention include vaccine efficacy, vaccine side effects, mistrust in healthcare, religious beliefs, and trust in information sources. Additionally, vaccination intentions are influenced by demographic factors such as age, gender, education, and region. Conclusions: The underlying factors of vaccine hesitancy are complex and context-specific, varying across time and socio-demographic variables. Vaccine hesitancy can also be influenced by other factors such as health inequalities, socioeconomic disadvantages, systemic racism, and level of exposure to misinformation online, with some factors being more dominant in certain countries than others. Therefore, strategies tailored to cultures and socio-psychological factors need to be developed to reduce vaccine hesitancy and aid informed decision-making.

Background: The process of wound healing in the socket include the healing of wounds in soft tissues, and healing of the bone. The herbal medicament widely used in the healing of different wounds. The benefit of Grape seed oil due to their anti-oxidant and anti-inflammatory effect. Objective: Histological evaluation the effects of local application of grape seeds oil in the healing process of dental socket after tooth extraction and compared the result with normal healing process. Patients and Methods: Thirty six New Zeland male rabbits were used in this study, the upper right central incisor was extracted for each rabbit ,then the rabbits were divided into 3 main groups ;Control group: 12 rabbits , the socket heal spontaneously , sponge group:12 rabbits ,the socket treated with absorbable hemostatic sponge and grape seed oil group: 12 rabbits, the socket treated with local application of 0.5 ml/Kg of B.W. grape seeds oil fixed by absorbable hemostatic sponge. Then each group were divided into two sub group according to the healing intervals 2 and 4 week (6 rabbits from each group). Histological evaluation performed by section stained with hematoxylin and eosin (H&E), and histomorphometric analysis for assessment of osteoclasts ,osteoblasts, osteocytes , trabecular no., trabecular area and marrow space area by Image J. software. Results: The histological and histomorphometric results of present study showed enhancement of healing process in grape seeds oil and sponge group after tooth extraction by activation of large number of osteoblasts, osteocytes and osteoclasts that started from apical part, then middle part finally in coronal part of the socket. Conclusion: Grape seed oil accelerate the healing process after locally treated tooth socket and assessed in new bone formation. DOI:https://doi.org/10.26505/DJM.17024670515

Background: The study showed that magnetized green tea has effects on bone regeneration, bone density and the amount of this effect depends on the intensity of the power and the frequency of the electromagnetic field emitted. The properties of green tea change when exposed to magnetic fields so that its contents change from metals and organic materials and be flexible and easy to penetrate the cell wall and increase the speed of proliferation. This change in properties is necessary for organ growth and the amount of effect depends on the strength of the electromagnetic field and the time of exposure. The study showed that is an improved in quality of the green tea when exposed to the electromagnetic field with significant changes in the minerals and organic matter .Therefore it’s penetration into cell wall would be facilitated, which can accelerate ordinary diffusion of green tea. That is vital for growth and development of different organs .Exposing the green tea to strong magnetic fields affect in the green tea mineral content , and its effects depend on the "strength of the magnetic field and exposure time". Objective: To study on the effect of consumption of magnetized green tea on bone density and osteoporosis in rats. Patients and Methods: In this study (14) rats were included and these divided into two groups, A and B "7 rats for each group" were included, Group A were fed normal water for 21 days, and group B were fed magnetized green tea for 21 days. The magnetize system that used to magnetized green tea, this consist of 7000 rolls of iron wire around iron tube where was magnetized green tea with 1400 rolls, which is connected to the continuous power supply "220 V". Digital Gauss meter was used to measure the magnetic flux which is equal to 0.9 (mT). After 21 daily consumption of the magnetized green tea, the bone density was measured by DXA scan device that is used to measure the bone mineral density" BMD", bone mineral content "BMC", T-score and Z-score. Comparing the result of "T-score, Z-score, BMD and BMC" between group A and B of the animals after 21 days of consumption the magnetized green tea. Results: The study shows an enhancement in the biological activity in rats that consumed the magnetized green tea, by repairing and turnover the bones as compared with other group that used normal water. Conclusion: It was concluded that the consumptions of magnetized green tea increase the ability of bone repair and turnover. DOI:https://doi.org/10.26505/DJM.17024430107

Background: The electromagnetic field used with industrial, and also simultaneous action of those fields on the intensity of bone turnover process in rats was estimated by means of analysis of densitometry. The obtained effect was dependent on frequency and power density of used electromagnetic fields .There was improved in quality of the water when exposed to the electromagnetic field with significant changes in the minerals and organic matter .Therefore it’s penetration into cell wall would be facilitated, which can accelerate ordinary diffusion of water. That is vital for growth and development of different organs .Exposing the water to strong magnetic fields affect in the water`s mineral content , and its effects depended on the "strength of the magnetic field and exposure time". Objective:To study the effect of depreciation the magnetizing water on bone density and osteoporosis for rats. Patients and Methods: In this study It was concluded (14) rat and divided to two groups, A and B "7 rats for each group". Group A feed normal water for 24 days, and group B feed magnetized water for 24 days. The magnetized system that used to magnetized the water consist of 4200 rolled silk around iron tube , and it is connected to the continuous power supply "220 V". and used Digital Gauss meter to measure the magnetic flux equal to 0.9mT. After 24 daily consumption of the magnetized water measure the bone density by DXA scan devise that use to measure the bone mineral density" BMD", bone mineral content "BMC", T-score and Z-score .Comparing the result of " T-score, Z-score, BMD and BMC " between group A and B of the animals after 24 days from consumption the magnetized water. Results: The study shows enhancing in the biological activity in rats that consumption the magnetized, by repairing and turnover the bones in comparing to other group that use normal water. Conclusion: The current study represented the consumptions of magnetized water increase the ability of bone repair and turnover.

This literature review emphasizes the impact of ethyl acetate organic solvent as surface treatment agent for 3-dimentional (3D) printed polymethyl methacrylate denture base and silicone soft liner on enhancing the strength of bonding of these materials. Over time, Denture soft liner materials have appeared as important components in prosthodontics, offering enhanced comfort, tissue adaptation for denture wearers and restore the inflamed and distorted mucosa. It is commonly agreed that the main drawback is debonding of the lining material from the 3D printed denture base. Therefore, there is a need for enhancing the strength of bonding of these materials [ABSTRACT FROM AUTHOR]

A service processing water supply for residential land use is a cornerstone to the success of all plans for economic and social development to bring it to the welfare of the required service, where the investment has been employed to improve the human and his service, lies in the attention to the safety of his health and social welfare, with a big return in increasing the productive capacity of society and development towards higher levels in human living. Problem lies in the lack of adoption of proper planning and successful completion of this vital service, task, and provided so as to ensure justice in the processing where not found in Iraq and in the study area, especially the standards and a real comprehensive studies planning cover all aspects of water supply service to residential areas, The city of Baghdad suffers from problems in justice processing water supply to revitalize the residential and scarves, and thus need to be clear and comprehensive study of this problem contributes to reducing the gap in the city of Baghdad and the rest of the provinces of the country.

Nimesulide is one of the types of non-steroidal anti-inflammatory drugs, widely used as analgesic and antipyretic. It is classified as class II drugs according to BCS guidance because of low solubility in water that leads to decrease in dissolution rate. So the objective of this study was to decrease particle size, increase solubility and dissolution rate of nimesulide by preparation of nimesulide nanoparticles using solvent/antisolvent precipitation method by addition of organic solution of drug onto the solution of stabilizer. The size of nimesulide nanoparticles were studied and considered by particle size analyzer, drug content and loading efficiency. The freeze dried nanoparticles were characterized by field emission electron microscope, X-Ray powder diffraction, differential scanning calorimetry and saturated solubility measurement. Tablet was manufactured by direct compression. The tablets were evaluated for drug release to measure the effect of nanoparticles on the dissolution improvement of drug.