Frontiers in digital health最新文献

{"title":"A simplified retriever to improve accuracy of phenotype normalizations by large language models.","authors":"Daniel B Hier, Thanh Son Do, Tayo Obafemi-Ajayi","doi":"10.3389/fdgth.2025.1495040","DOIUrl":"10.3389/fdgth.2025.1495040","url":null,"abstract":"<p><p>Large language models have shown improved accuracy in phenotype term normalization tasks when augmented with retrievers that suggest candidate normalizations based on term definitions. In this work, we introduce a simplified retriever that enhances large language model accuracy by searching the Human Phenotype Ontology (HPO) for candidate matches using contextual word embeddings from BioBERT without the need for explicit term definitions. Testing this method on terms derived from the clinical synopses of Online Mendelian Inheritance in Man (OMIM^®), we demonstrate that the normalization accuracy of GPT-4o increases from a baseline of 62% without augmentation to 85% with retriever augmentation. This approach is potentially generalizable to other biomedical term normalization tasks and offers an efficient alternative to more complex retrieval methods.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1495040"},"PeriodicalIF":3.2,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913805/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative analysis of large language models on clinical questions for autoimmune diseases.","authors":"Jing Chen, Juntao Ma, Jie Yu, Weiming Zhang, Yijia Zhu, Jiawei Feng, Linyu Geng, Xianchi Dong, Huayong Zhang, Yuxin Chen, Mingzhe Ning","doi":"10.3389/fdgth.2025.1530442","DOIUrl":"10.3389/fdgth.2025.1530442","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) has made great strides. To explore the potential of Large Language Models (LLMs) in providing medical services to patients and assisting physicians in clinical practice, our study evaluated the performance in delivering clinical questions related to autoimmune diseases.</p><p><strong>Methods: </strong>46 questions related to autoimmune diseases were input into ChatGPT 3.5, ChatGPT 4.0, and Gemini. The responses were then evaluated by rheumatologists based on five quality dimensions: relevance, correctness, completeness, helpfulness, and safety. Simultaneously, the responses were assessed by laboratory specialists across six medical fields: concept, clinical features, report interpretation, diagnosis, prevention and treatment, and prognosis. Finally, statistical analysis and comparisons were performed on the performance of the three chatbots in the five quality dimensions and six medical fields.</p><p><strong>Results: </strong>ChatGPT 4.0 outperformed both ChatGPT 3.5 and Gemini across all five quality dimensions, with an average score of 199.8 ± 10.4, significantly higher than ChatGPT 3.5 (175.7 ± 16.6) and Gemini (179.1 ± 11.8) (<i>p</i> = 0.009 and <i>p</i> = 0.001, respectively). The average performance differences between ChatGPT 3.5 and Gemini across these five dimensions were not statistically significant. Specifically, ChatGPT 4.0 demonstrated superior performance in relevance (<i>p</i> < 0.0001, <i>p</i> < 0.0001), completeness (<i>p</i> < 0.0001, <i>p</i> = 0.0006), correctness (<i>p</i> = 0.0001, <i>p</i> = 0.0002), helpfulness (<i>p</i> < 0.0001, <i>p</i> < 0.0001), and safety (<i>p</i> < 0.0001, <i>p</i> = 0.0025) compared to both ChatGPT 3.5 and Gemini. Furthermore, ChatGPT 4.0 scored significantly higher than both ChatGPT 3.5 and Gemini in medical fields such as report interpretation (<i>p</i> < 0.0001, <i>p</i> = 0.0025), prevention and treatment (<i>p</i> < 0.0001, <i>p</i> = 0.0103), prognosis (<i>p</i> = 0.0458, <i>p</i> = 0.0458).</p><p><strong>Conclusions: </strong>This study demonstrates that ChatGPT 4.0 significantly outperforms ChatGPT 3.5 and Gemini in addressing clinical questions related to autoimmune diseases, showing notable advantages across all five quality dimensions and six clinical domains. These findings further highlight the potential of large language models in enhancing healthcare services.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1530442"},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enterprise-led internet healthcare provision in China: insights from a leading platform.","authors":"Li Wang, Dan Liang, Hengqian HuangFu, Changwen Ke, Shaolong Wu, Yingsi Lai","doi":"10.3389/fdgth.2025.1491183","DOIUrl":"10.3389/fdgth.2025.1491183","url":null,"abstract":"<p><strong>Background: </strong>China's healthcare resources are limited and unevenly distributed, with a notable urban-rural gap. Enterprise-led internet healthcare platforms have become an important solution for optimizing resource allocation, improving accessibility, and enhancing efficiency in mainland China. However, detailed analysis of their online consultation services from both healthcare provider and patient perspectives is still lacking.</p><p><strong>Objective: </strong>The online consultation data of an enterprise-led internet healthcare platform was depicted and analyzed to understand the temporal trend and current situation of enterprise-led internet healthcare development in mainland China, which provided insights for the further development of internet healthcare.</p><p><strong>Methods: </strong>We gathered information from an enterprise-led internet healthcare platform (i.e., Good Doctor Online) covering the period from January 2008 to December 2022, including the characteristics of doctors, healthcare institutions, and patients. Based on the above data, we sketched and analyzed the situation of online consultation services provided by the enterprise-led internet healthcare platform in mainland China.</p><p><strong>Results: </strong>A total of 149,890 doctors from 7,584 healthcare institutions provided 40,462,801 online consultations from January 2008 to December 2022. Doctors and healthcare institutions providing online consultation services were primarily distributed in the economically developed eastern and southern provinces of China. Doctors with intermediate (30.15%) and senior titles (58.12%) were the main providers of online consultations and most doctors were from tertiary hospitals (88.18%). The consultation price {<i>median</i> [interquartile range (<i>IQR</i>)]} was 49.00 (15.00, 100.00) RMB. The health issues with the highest consultation frequency included upper respiratory tract infections or fever (16.19%), gynecological disorders (11.98%), and skin diseases (8.65%), with variations in gender and age. The age distribution of patients showed two peaks in age groups <5 years and 20-39 years, with the median age (IQR) 29.00 (19.00-43.00) years.</p><p><strong>Conclusions: </strong>Enterprise-led internet healthcare platforms enhance access to care and reduce offline resource strain, especially during COVID-19. They mainly address non-urgent conditions but cannot fully replace in-person care. Policies should focus on increasing elderly participation, engaging senior doctors, optimizing male-oriented services, expanding access to underserved areas, standardizing pricing, and broadening insurance reimbursement coverage to improve equity and sustainability.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1491183"},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911379/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital health tools applications in frail older adults-a review article.","authors":"Natthanaphop Isaradech, Wachiranun Sirikul","doi":"10.3389/fdgth.2025.1495135","DOIUrl":"10.3389/fdgth.2025.1495135","url":null,"abstract":"<p><strong>Introduction: </strong>Frailty is a common degenerative condition highly prevalent in adults over 65 years old. A frail person has a higher risk of morbidities and mortality when exposed to health-related stressors. However, frailty is a reversible state when it is early diagnosed. Studies have shown that frail people who participated in an exercise prescription have a greater chance to transition from frail to fit. Additionally, with a rapid advancement of technology, a vast majority of studies are supporting evidence regarding the digital health tools application on frail population in recent years.</p><p><strong>Methods: </strong>This review comprehensively summarizes and discusses about technology application in frail persons to capture the current knowledge gaps and propose future research directions to support additional research in this field. We used PubMed to search literature (2012-2023) with pre-specified terms. Studies required older adults using digital tools for frailty comparison, association, or prediction and we excluded non-English studies and those lacking frailty comparison or digital tool use.</p><p><strong>Results: </strong>Our review found potential etiognostic factors in trunk, gait, upper-extremity, and physical activity parameters for diagnosing frailty using digital tools in older adults.</p><p><strong>Conclusion: </strong>Studies suggest exercise improves frailty status, emphasizing the need for integrated therapeutic platforms and personalized prevention recommendations.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1495135"},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911361/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143651734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of artificial intelligence for reverse referral between a hospital emergency department and a primary urgent care center.","authors":"Yolanda Taules, Silvia Gros, Maria Viladrosa, Natàlia Llorens, Sílvia Solis, Oriol Yuguero","doi":"10.3389/fdgth.2025.1546467","DOIUrl":"10.3389/fdgth.2025.1546467","url":null,"abstract":"<p><strong>Background: </strong>The demand for immediate care in emergency departments (EDs) has risen since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic.</p><p><strong>Objective: </strong>Test the ability of AI to promote reverse referral and to provide patient education.</p><p><strong>Methods: </strong>Pilot study that included patients presenting to our Hospital Emergency Department (HED) with a non severe disease and who met the inclusion criteria. The participants were asked to answer a series of questions using an electronic device and receive a recommendation for health attention. Then, patients could choose to either remain in the hospital or leave.</p><p><strong>Results: </strong>427 patients finally participated in the pilot study. Within this population, 49.5% were women, and the mean patient age was 37.5 years. Mediktor recommended reverse referral to urgent care in 43.6%. Our results demonstrate that the tool is safe and provides accurate patient screening, correctly distinguishing between those who should continue to wait for HED care and those for whom an urgent care center is adequate.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1546467"},"PeriodicalIF":3.2,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911458/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143652280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Digital twins in medicine-transition from theoretical concept to tool used in everyday care.","authors":"Stephen Gilbert, David Drummond, Fabienne Cotte, Tjalf Ziemssen","doi":"10.3389/fdgth.2025.1573727","DOIUrl":"10.3389/fdgth.2025.1573727","url":null,"abstract":"","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1573727"},"PeriodicalIF":3.2,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11903405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of markerless video-based gait analysis using pose estimation in toddlers with and without neurodevelopmental disorders.","authors":"Jeffrey T Anderson, Jan Stenum, Ryan T Roemmich, Rujuta B Wilson","doi":"10.3389/fdgth.2025.1542012","DOIUrl":"10.3389/fdgth.2025.1542012","url":null,"abstract":"<p><strong>Introduction: </strong>The onset of locomotion is a critical motor milestone in early childhood and increases engagement with the environment. Toddlers with neurodevelopmental disabilities often have atypical motor development that impacts later outcomes. Video-based gait analysis using pose estimation offers an alternative to standardized motor assessments which are subjective and difficult to ascertain in some populations, yet very little work has been done to determine its accuracy in young children. To fill this gap, this study aims to assess the feasibility and accuracy of pose estimation for gait analysis in children with a range of developmental levels.</p><p><strong>Methods: </strong>We analyzed the overground gait of 112 toddlers (M: 30 months, SD: 8 months) with and without developmental disabilities using the ProtoKinetics Zeno Walkway system. Simultaneously recorded videos were processed in OpenPose to perform pose estimation and a custom MATLAB workflow to calculate average spatiotemporal gait parameters. Pearson correlations were used to compare OpenPose with the Zeno Walkway for velocity, step length, and step time. A Bland-Altman analysis (difference vs. average) was used to assess the agreement between methodologies and determine the difference of means. Developmental levels were assessed using the Mullen Scales of Early Learning.</p><p><strong>Results: </strong>Our analysis included children with autism (<i>n</i> = 77), non-autism developmental concerns (<i>n</i> = 6), tuberous sclerosis complex (<i>n</i> = 13), 22q deletion (<i>n</i> = 1), and typical development (<i>n</i> = 15). Mullen early learning composite scores ranged from 49 to 95 (m = 80.91, sd = 26.68). Velocity (r = 0.87, <i>p</i> < 0.0001), step length (r = 0.79, <i>p</i> < 0.0001), and step time (r = 0.96, <i>p</i> < 0.0001) were all highly correlated between OpenPose and the Zeno Walkway, with an absolute difference of means of 0.04 m/s, 0.03 m, and 0.01 s, respectively.</p><p><strong>Discussion: </strong>Our results suggest that video-based gait analysis using pose estimation is accurate in toddlers with a range of developmental levels. Video-based gait analysis is low cost and can be implemented for remote data collection in natural environments such as a participant's home. These advantages open possibilities for using repeated measures to increase our knowledge of how gait ability changes over time in pediatric populations and improve clinical screening tools, particularly in those with neurodevelopmental disabilities who exhibit motor impairments.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1542012"},"PeriodicalIF":3.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11893606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intention to use personal health records and associated factors among healthcare providers in southwest Oromia region referral hospitals, Ethiopia: using the modified unified theory of acceptance and use technology 2 model.","authors":"Geleta Nenko Dube, Mulusew Andualem Asemahagn, Yared Mulu, Habtamu Alganeh Guadie, Mohammedjud Hassen Ahmed, Agmasie Damtew Walle, Getu Kassa Bitacha, Temesgen Ayenew Alameraw, Nega Abebe Meshasha","doi":"10.3389/fdgth.2025.1368588","DOIUrl":"10.3389/fdgth.2025.1368588","url":null,"abstract":"<p><strong>Introduction: </strong>A well-informed decision needs the collection of accurate and organized data, which is becoming more essential in the healthcare industry due to the increasing integration of various technologies. The literature has revealed that the magnitude of intention to use personal health records among healthcare providers is low. Consequently, this study aimed to assess healthcare providers' intentions to use personal health records and its factors in Ethiopia.</p><p><strong>Methods: </strong>A facility-based cross-sectional study was conducted among 781 healthcare providers in referral hospitals in the Southwest Oromia region, Ethiopia. A simple sampling technique was used to select the study participants among healthcare providers. A pretested self-administered questionnaire was used to collect the data. The degree of correlation between exogenous and endogenous variables was described and validated using structural equation modeling using AMOS 26.</p><p><strong>Results: </strong>The proportion of intention to use personal health records was 57.6%, 95% CI (53.9-61.2). Factors positively associated with intention to use personal health records were performance expectancy (β = 0.325, <i>P</i> < 0.01), effort expectancy (β = 0.289, <i>P</i> < 0.01), social influence (β = 0.216, <i>P</i> < 0.01), and facilitating condition (β = 0.242, <i>P</i> < 0.01). Age (β = 0.269, <i>P</i> = 0.040, β = 0.326, <i>P</i> < 0.001) positively moderated the relationship between performance expectancy, facilitating conditions to intention to use personal health records.</p><p><strong>Conclusions: </strong>In general, healthcare providers' intention to use personal health records were promising. Healthcare providers' intentions to use personal health records were significantly influenced by performance expectancy, effort expectancy, social influence, and facilitating conditions. Hence, implementers need to give priority to enhancing the provision of a better system, the knowledge and skills of healthcare providers, and awareness creation among staff by providing continuous training.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1368588"},"PeriodicalIF":3.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11893608/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Levelling up as a fair solution in AI enabled cancer screening.","authors":"Sahar Abdulrahman, Markus Trengove","doi":"10.3389/fdgth.2025.1540982","DOIUrl":"10.3389/fdgth.2025.1540982","url":null,"abstract":"","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1540982"},"PeriodicalIF":3.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11893865/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empowering pediatric, adolescent, and young adult patients with cancer utilizing generative AI chatbots to reduce psychological burden and enhance treatment engagement: a pilot study.","authors":"Joe Hasei, Mana Hanzawa, Akihito Nagano, Naoko Maeda, Shinichirou Yoshida, Makoto Endo, Nobuhiko Yokoyama, Motoharu Ochi, Hisashi Ishida, Hideki Katayama, Tomohiro Fujiwara, Eiji Nakata, Ryuichi Nakahara, Toshiyuki Kunisada, Hirokazu Tsukahara, Toshifumi Ozaki","doi":"10.3389/fdgth.2025.1543543","DOIUrl":"10.3389/fdgth.2025.1543543","url":null,"abstract":"<p><strong>Background: </strong>Pediatric and adolescent/young adult (AYA) cancer patients face profound psychological challenges, exacerbated by limited access to continuous mental health support. While conventional therapeutic interventions often follow structured protocols, the potential of generative artificial intelligence (AI) chatbots to provide continuous conversational support remains unexplored. This study evaluates the feasibility and impact of AI chatbots in alleviating psychological distress and enhancing treatment engagement in this vulnerable population.</p><p><strong>Methods: </strong>Two age-appropriate AI chatbots, leveraging GPT-4, were developed to provide natural, empathetic conversations without structured therapeutic protocols. Five pediatric and AYA cancer patients participated in a two-week intervention, engaging with the chatbots via a messaging platform. Pre- and post-intervention anxiety and stress levels were self-reported, and usage patterns were analyzed to assess the chatbots' effectiveness.</p><p><strong>Results: </strong>Four out of five participants reported significant reductions in anxiety and stress levels post-intervention. Participants engaged with the chatbot every 2-3 days, with sessions lasting approximately 10 min. All participants noted improved treatment motivation, with 80% disclosing personal concerns to the chatbot they had not shared with healthcare providers. The 24/7 availability particularly benefited patients experiencing nighttime anxiety.</p><p><strong>Conclusions: </strong>This pilot study demonstrates the potential of generative AI chatbots to complement traditional mental health services by addressing unmet psychological needs in pediatric and AYA cancer patients. The findings suggest these tools can serve as accessible, continuous support systems. Further large-scale studies are warranted to validate these promising results.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1543543"},"PeriodicalIF":3.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11893593/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}