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JMIR Medical Informatics|December 20, 2021
Artificial Intelligence in Predicting Cardiac Arrest: Scoping ReviewAsma Alamgir, Osama Mousa, Zubair Shah
JMIR Medical Informatics|July 9, 2026
Quantifying the Predictive Power of Social Determinants of Health in Cardiovascular Disease and Type 2 Diabetes Progression Using XGBoost: Retrospective Cohort StudyHielke Muizelaar, Marcel Haas, Maarten van Aken, et al.
JMIR Medical Informatics|July 10, 2026
Exploring the Role of Large Language Models in Primary Care: Qualitative Study of Physicians in the United States and the NetherlandsIlse Super, Harinder Bawa, Onur Asan
JMIR Medical Informatics|March 23, 2026
Explainable Machine Learning for Assessing Digital Health Literacy in Older Adults: Validation and Development of a Two-Stage Model Integrating Performance-Based and Self-Assessed IndicatorsChoonghee Park, Jiyeon Park, Seora Kim, et al.
JMIR Medical Informatics|March 24, 2026
Influencing Factors of Mobile Health Apps in Kidney Transplant Care: Systematic Review Using the Consolidated Framework for Implementation ResearchYingtian Jia, Shaobo Guo, Xinran Yang, et al.
JMIR Medical Informatics|April 2, 2026
Stakeholder Perspectives on Affinity Domains in Digital Health Interoperability: Qualitative StudyJan Bruthans, Petra Hospodková, Ilona Fejfarová
JMIR Medical Informatics|April 2, 2026
An Intelligent Interactive Management Platform for Rheumatoid Arthritis Care: Real-World Observational StudyZiyun Zhang, Xinyue Zhang, Li Zhang, et al.
JMIR Medical Informatics|April 17, 2026
Stress Hyperglycemia Ratio and the Risk of Sepsis in Patients With Heart Failure: Retrospective Cohort Study From Medical Information Mart for Intensive Care-IVXianzhen Cai, Baoxin Yan, Jinhao Chen, et al.
JMIR Medical Informatics|May 6, 2026
General Practitioners and Pharmacists' Perspectives on Electronic Prescribing for Multidose Drug Dispensing: Mixed Methods StudyAnn-Kristin Sørvik Rasmussen, Synne Mari Trælnes, Stian Skogly, et al.
JMIR Medical Informatics|May 4, 2026
Large Language Model Automated Extraction of Clinical Signs and Symptoms From Emergency Department Reports for Machine Learning Prediction Models: Development and Validation StudyAnoeska Schipper, Peter Belgers, Rory David O'Connor, et al.
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