Yearbook of medical informatics最新文献

{"title":"Consumer Informatics and One Health: Shifting the Focus from the Individual to the Globe. Findings from the Yearbook 2023 Section on Education and Consumer Health Informatics.","authors":"Pascal Staccini, Annie Y S Lau","doi":"10.1055/s-0043-1768749","DOIUrl":"10.1055/s-0043-1768749","url":null,"abstract":"<p><strong>Objective: </strong>To summarise the state of the art during the year 2022 in consumer health informatics and education, with a special emphasis on \"One Health\".</p><p><strong>Methods: </strong>We conducted a systematic search of articles published in PubMed. We build queries to merge terms related to \"consumer health informatics\", \"one health\", and \"digital\". We retrieved 94 potential articles for review. These articles were screened according to topic relevance and 12 were selected for consideration of best paper candidates, which were then presented to a panel of international experts for full paper review and scoring. The top five papers were discussed in a consensus meeting. Three papers received the highest score from the expert panel, and these papers were selected to be representative papers on consumer informatics for exploring one health from consumer perspective in the year 2022.</p><p><strong>Results: </strong>Bibliometrics analysis conducted on words found in abstracts of the 12 candidate papers revealed four clusters of articles, where clustering outcomes explained 96.91% of the dispersion. The first cluster composes three papers related to patient engagement in primary care practices, using digital-delivered diabetes prevention programmes, or exploring citizen involvement in co-designing environmental projects (such as air pollution exposure and health). The second cluster represents four papers related to digital health literacy and consumer behavior, such as digital vaccine literacy, and food labelling influences and whether displaying Nutri- and Eco-Score at food product level led to improved consumer choices. The third cluster consists of two papers exploring strategies to involve citizens in various science projects while analyzing the quality of citizen-collected data (e.g., mosquito bites or gastropod community dataset). The last cluster contains three papers related to the relationships between human behavior with their environment and their contribution to citizen science projects (e.g., biological water quality in the Netherlands distribution, composition, abundance of debris across sandy beaches in Australia and its regions, urbanization and reptile biodiversity across Florida).</p><p><strong>Conclusion: </strong>Traditionally, consumer health informatics focuses on providing individuals with tools and resources to actively manage their own health. By incorporating a global health (or one health) perspective, our field is now at a crossroad, demanding us to think beyond the individual and challenging us to instill the thinking that our actions not only have consequences on the individual but also on the population and the environment. Perhaps this is also a reflective time for the consumer informatics field, to consider shifting the focus from the individual to one that is more aligned with one health, helping consumers gain awareness of how their actions impact on the individual, the population and the enviro","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"32 1","pages":"158-168"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040624","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":"Intersecting Pathways in Bioinformatics and Translational Informatics: A One Health Perspective on Key Contributions and Future Directions.","authors":"Mary Lauren Benton, Scott McGrath","doi":"10.1055/s-0043-1768745","DOIUrl":"10.1055/s-0043-1768745","url":null,"abstract":"<p><strong>Objectives: </strong>To identify and summarize the top bioinformatics and translational informatics (BTI) papers published in 2022 for the International Medical Informatics Association (IMIA) Yearbook 2023.</p><p><strong>Methods: </strong>We conducted a comprehensive literature search to identify the top BTI papers, resulting in a set of ten candidate papers. The candidates were reviewed by the section co-editors and external reviewers to select the top three papers from 2022.</p><p><strong>Results: </strong>From a total of 558 papers, we identified a final candidate list of ten BTI papers for peer-review. These papers apply new statistical frameworks and experimental designs to better capture individual variability in disease and incorporate data that captures differences between single cells and across environmental exposures. In addition, they highlight the importance of model generalization across diverse cohorts and scalability to large medical centers.</p><p><strong>Conclusions: </strong>We note several important trends in the candidate top BTI papers this year, including a continued focus on developing accurate and scalable computational models to predict disease risk across diverse cohorts and new strategies to capture the molecular heterogeneity of disease.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"32 1","pages":"99-103"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751152/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040645","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":"Contents IMIA Yearbook of Medical Informatics 2023","authors":"J. Li, K. Fultz, F. Mougin, L. F. Soualmia, Survey K. Cooper, M. Clarke, J. B. Clayton, M. L. Benton, S. P. McGrath, Survey S. Aneja, A. Avesta, H. Xu, L. O. Machado, J. L. Warner, D. Patt","doi":"10.1055/s-0043-1768763","DOIUrl":"https://doi.org/10.1055/s-0043-1768763","url":null,"abstract":"","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139352215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cover IMIA Yearbook of Medical Informatics 2023","authors":"","doi":"10.1055/s-0043-1768736","DOIUrl":"https://doi.org/10.1055/s-0043-1768736","url":null,"abstract":"","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139352906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IMIA Member Societies *as at November 2023","authors":"","doi":"10.1055/s-0043-1768761","DOIUrl":"https://doi.org/10.1055/s-0043-1768761","url":null,"abstract":"","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139352644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine and Deep Learning Dominate Recent Innovations in Sensors, Signals and Imaging Informatics.","authors":"Christian Baumgartner, Leticia Rittner, Thomas M Deserno","doi":"10.1055/s-0043-1768743","DOIUrl":"10.1055/s-0043-1768743","url":null,"abstract":"<p><strong>Objectives: </strong>This review presents research papers highlighting notable developments and trends in sensors, signals, and imaging informatics (SSII) in 2022.</p><p><strong>Method: </strong>We performed a bibliographic search in PubMed combining Medical Subject Heading (MeSH) terms and keywords to create particular queries for sensors, signals, and imaging informatics. Only papers published in journals containing greater than three articles in the search query were considered. Using a three-point Likert scale (1 = not include, 2 = perhaps include, 3 = include), we reviewed the titles and abstracts of all database results. Only articles that scored three times Likert scale 3, or two times Likert scale 3, and one time Likert scale 2 were considered for full paper review. On this pre-selection, only papers with a total of at least eight points of the three section co-editors were considered for external review. Based on the external reviewers, we selected the top two papers representing significant research in SSII.</p><p><strong>Results: </strong>Among the 469 returned papers published in 2022 in the various areas of SSII, 90, 31, and 348 papers for sensors, signals, and imaging informatics, and then, the full review process selected the two best papers. From the 469 papers, the section co-editors identified 29 candidate papers with at least 8 Likert points in total, of which 9 were nominated as the best contributions after a full paper assessment. Five external reviewers evaluated the nominated papers, and the two highest-scoring papers were selected based on the overall scores of all external reviewers. A consensus of the International Medical Informatics Association (IMIA) Yearbook editorial board finally approved the nominated papers. Machine and deep learning-based techniques continue to be the dominant theme in this field.</p><p><strong>Conclusions: </strong>Sensors, signals, and imaging informatics is a dynamic field of intensive research with increasing practical applications to support medical decision-making on a personalized basis.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"32 1","pages":"282-285"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751153/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040670","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":"Security and Privacy in Machine Learning for Health Systems: Strategies and Challenges.","authors":"Erikson J de Aguiar, Caetano Traina, Agma J M Traina","doi":"10.1055/s-0043-1768731","DOIUrl":"10.1055/s-0043-1768731","url":null,"abstract":"<p><strong>Objectives: </strong>Machine learning (ML) is a powerful asset to support physicians in decision-making procedures, providing timely answers. However, ML for health systems can suffer from security attacks and privacy violations. This paper investigates studies of security and privacy in ML for health.</p><p><strong>Methods: </strong>We examine attacks, defenses, and privacy-preserving strategies, discussing their challenges. We conducted the following research protocol: starting a manual search, defining the search string, removing duplicated papers, filtering papers by title and abstract, then their full texts, and analyzing their contributions, including strategies and challenges. Finally, we collected and discussed 40 papers on attacks, defense, and privacy.</p><p><strong>Results: </strong>Our findings identified the most employed strategies for each domain. We found trends in attacks, including universal adversarial perturbation (UAPs), generative adversarial network (GAN)-based attacks, and DeepFakes to generate malicious examples. Trends in defense are adversarial training, GAN-based strategies, and out-of-distribution (OOD) to identify and mitigate adversarial examples (AE). We found privacy-preserving strategies such as federated learning (FL), differential privacy, and combinations of strategies to enhance the FL. Challenges in privacy comprehend the development of attacks that bypass fine-tuning, defenses to calibrate models to improve their robustness, and privacy methods to enhance the FL strategy.</p><p><strong>Conclusions: </strong>In conclusion, it is critical to explore security and privacy in ML for health, because it has grown risks and open vulnerabilities. Our study presents strategies and challenges to guide research to investigate issues about security and privacy in ML applied to health systems.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"32 1","pages":"269-281"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751106/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040674","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":"Telehealth as a Component of One Health: a Position Paper.","authors":"Arindam Basu, Vije Kumar Rajput, Marcia Ito, Prasad Ranatunga, Craig Kuziemsky, Gumindu Kulatunga, Inga Hunter, Najeeb Al-Shorbaji, Shashi Gogia, Sriram Iyengar","doi":"10.1055/s-0043-1768728","DOIUrl":"10.1055/s-0043-1768728","url":null,"abstract":"<p><strong>Introduction: </strong>One Health (OH) refers to the integration of human, animal, and ecosystem health within one framework in the context of zoonoses, antimicrobial resistance and stewardship, and food security. Telehealth refers to distance delivery of healthcare. A systems approach is central to both One Health and telehealth, and telehealth can be a core component of One Health. Here we explain how telehealth might be integrated into One Health.</p><p><strong>Methods: </strong>We have considered antimicrobial resistance (AMR) as a use case where both One Health and telehealth can be used for coordination among the farming sector, the veterinary services, and human health providers to mitigate the risk of AMR. We conducted a narrative review of the literature to develop a position on the inter-relationships between telehealth and One Health. We have summarised how telehealth can be incorporated within One Health.</p><p><strong>Results: </strong>Clinicians have used telehealth to address antimicrobial resistance, zoonoses, food borne infection, improvement of food security and antimicrobial stewardship. We identified little existing evidence in support of the usage of telehealth within a One Health paradigm, although in isolation, both are useful for the same purpose, i.e., mitigation of the significant public health risks posed by zoonoses, food borne infections, and antimicrobial resistance.</p><p><strong>Conclusions: </strong>It is possible to integrate telehealth within a One Health framework to develop effective inter-sectoral communication essential for the mitigation and addressing of zoonoses, food security, food borne infection containment and antimicrobial stewardship. More research is needed to substantiate and investigate this model of healthcare.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"32 1","pages":"19-26"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751139/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040675","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":"Transforming Clinical Information Systems: Empowering Healthcare through Telemedicine, Data Science, and Artificial Intelligence Applications.","authors":"Werner O Hackl, Sabrina B Neururer, Bernhard Pfeifer","doi":"10.1055/s-0043-1768756","DOIUrl":"10.1055/s-0043-1768756","url":null,"abstract":"<p><strong>Objective: </strong>In this synopsis, the editors of the Clinical Information Systems (CIS) section of the IMIA Yearbook of Medical Informatics overview recent research and propose a selection of best papers published in 2022 in the CIS field.</p><p><strong>Methods: </strong>The editors follow a systematic approach to gather relevant articles and select the best papers for the section. This year, they updated the query to incorporate the topic of telemedicine and removed search terms related to geographic information systems. The revised query resulted in a larger number of identified papers, necessitating the appointment of a third section editor to handle the increased workload. The editors narrowed the initial pool of articles to 15 candidate papers through a multi-stage selection process. At least seven independent reviews were collected for each candidate paper, and a selection meeting with the IMIA Yearbook editorial board led to the final selection of the best papers for the CIS section.</p><p><strong>Results: </strong>The query was carried out in mid-January 2023 and retrieved a deduplicated result set of 5,206 articles from 1,500 journals. This year, 15 papers were nominated as candidates, and four were finally selected as the best papers in the CIS section.Including telemedicine in the query resulted in a substantial increase in the number of papers found. The analysis highlights the growing convergence between clinical information systems and telemedicine, with mobile health (mHealth) technologies and data science applications gaining prominence. The selected candidate papers emphasize the practical impact of research efforts, focusing on patient-centric outcomes and benefits, including intelligent mobile health monitoring systems and AI-assisted decision-making in healthcare.</p><p><strong>Conclusions: </strong>Looking ahead, the field of CIS is expected to continue evolving, driven by advances in telemedicine, mHealth technologies, data science, and AI integration, leading to more efficient, patient-oriented, and intelligent healthcare systems and overall improvement of global healthcare outcomes.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"32 1","pages":"127-137"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751109/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139040676","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":"Health Equity in Clinical Research Informatics.","authors":"Sigurd Maurud, Silje H Henni, Anne Moen","doi":"10.1055/s-0043-1768720","DOIUrl":"10.1055/s-0043-1768720","url":null,"abstract":"<p><strong>Objectives: </strong>Through a scoping review, we examine in this survey what ways health equity has been promoted in clinical research informatics with patient implications and especially published in the year of 2021 (and some in 2022).</p><p><strong>Method: </strong>A scoping review was conducted guided by using methods described in the Joanna Briggs Institute Manual. The review process consisted of five stages: 1) development of aim and research question, 2) literature search, 3) literature screening and selection, 4) data extraction, and 5) accumulate and report results.</p><p><strong>Results: </strong>From the 478 identified papers in 2021 on the topic of clinical research informatics with focus on health equity as a patient implication, 8 papers met our inclusion criteria. All included papers focused on artificial intelligence (AI) technology. The papers addressed health equity in clinical research informatics either through the exposure of inequity in AI-based solutions or using AI as a tool for promoting health equity in the delivery of healthcare services. While algorithmic bias poses a risk to health equity within AI-based solutions, AI has also uncovered inequity in traditional treatment and demonstrated effective complements and alternatives that promotes health equity.</p><p><strong>Conclusions: </strong>Clinical research informatics with implications for patients still face challenges of ethical nature and clinical value. However, used prudently-for the right purpose in the right context-clinical research informatics could bring powerful tools in advancing health equity in patient care.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":" ","pages":"138-145"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10751137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9755301","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}