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Identifying Asthma-Related Symptoms From Electronic Health Records Using a Hybrid Natural Language Processing Approach Within a Large Integrated Health Care System: Retrospective Study
JMIR AI 2025;4(1):e69132
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| 9164 | 0 | 0 | |
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Forecasting Artificial Intelligence Trends in Health Care: Systematic International Patent Analysis
JMIR AI 2023;2(1):e47283
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| 3533 | 81 | 5 | |
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Assessing Elevated Blood Glucose Levels Through Blood Glucose Evaluation and Monitoring Using Machine Learning and Wearable Photoplethysmography Sensors: Algorithm Development and Validation
JMIR AI 2023;2(1):e48340
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| 2431 | 16 | 6 | |
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Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study
JMIR AI 2023;2(1):e44358
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| 2309 | 11 | 21 | |
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Adolescents’ Well-being While Using a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Evidence From a Longitudinal Study
JMIR AI 2022;1(1):e38171
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| 1729 | 4 | 13 | |
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Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review
JMIR AI 2023;2(1):e42936
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| 1572 | 4 | 30 | |
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Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study
JMIR AI 2025;4(1):e58670
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| 1383 | 13 | 12 | |
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Predicting Treatment Interruption Among People Living With HIV in Nigeria: Machine Learning Approach
JMIR AI 2023;2(1):e44432
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| 1311 | 3 | 5 | |
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The Application of Artificial Intelligence in Health Care Resource Allocation Before and During the COVID-19 Pandemic: Scoping Review
JMIR AI 2023;2(1):e38397
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| 1276 | 1 | 19 | |
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How Explainable Artificial Intelligence Can Increase or Decrease Clinicians’ Trust in AI Applications in Health Care: Systematic Review
JMIR AI 2024;3(1):e53207
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| 1275 | 0 | 28 | |
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Patient Embeddings From Diagnosis Codes for Health Care Prediction Tasks: Pat2Vec Machine Learning Framework
JMIR AI 2023;2(1):e40755
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| 1181 | 9 | 5 | |
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Comparing the Efficacy and Efficiency of Human and Generative AI: Qualitative Thematic Analyses
JMIR AI 2024;3(1):e54482
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| 1130 | 0 | 21 | |
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Preparing for an Artificial Intelligence–Enabled Future: Patient Perspectives on Engagement and Health Care Professional Training for Adopting Artificial Intelligence Technologies in Health Care Settings
JMIR AI 2023;2(1):e40973
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| 1063 | 8 | 18 | |
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Developing Ethics and Equity Principles, Terms, and Engagement Tools to Advance Health Equity and Researcher Diversity in AI and Machine Learning: Modified Delphi Approach
JMIR AI 2023;2(1):e52888
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| 994 | 15 | 16 | |
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Evaluating the Diagnostic Performance of Symptom Checkers: Clinical Vignette Study
JMIR AI 2024;3(1):e46875
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| 904 | 6 | 3 | |
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Evaluating Literature Reviews Conducted by Humans Versus ChatGPT: Comparative Study
JMIR AI 2024;3(1):e56537
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| 901 | 8 | 17 | |
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Toward Clinical Generative AI: Conceptual Framework
JMIR AI 2024;3(1):e55957
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| 899 | 7 | 24 | |
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Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study
JMIR AI 2024;3(1):e60020
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| 827 | 0 | 14 | |
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Application of Artificial Intelligence to the Monitoring of Medication Adherence for Tuberculosis Treatment in Africa: Algorithm Development and Validation
JMIR AI 2023;2(1):e40167
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| 815 | 9 | 17 | |
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Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study
JMIR AI 2023;2(1):e47353
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| 738 | 6 | 10 | |
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Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study
JMIR AI 2023;2(1):e45000
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| 736 | 7 | 5 | |
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Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study
JMIR AI 2023;2(1):e46487
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| 715 | 3 | 11 | |
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Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial
JMIR AI 2024;3(1):e52615
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| 705 | 31 | 8 | |
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Perceptions of Family Physicians About Applying AI in Primary Health Care: Case Study From a Premier Health Care Organization
JMIR AI 2024;3(1):e40781
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| 644 | 2 | 8 | |
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A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach
JMIR AI 2023;2(1):e42337
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| 644 | 2 | 2 | |