| 1.
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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| 3028 | 0 | 122 | |
| 2.
Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial
JMIR AI 2023;2(1):e49023
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| 1133 | 9 | 92 | |
| 3.
Comparing the Efficacy and Efficiency of Human and Generative AI: Qualitative Thematic Analyses
JMIR AI 2024;3(1):e54482
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| 1643 | 0 | 54 | |
| 4.
Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review
JMIR AI 2023;2(1):e42936
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| 1978 | 4 | 47 | |
| 5.
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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| 3080 | 11 | 42 | |
| 6.
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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| 2603 | 13 | 40 | |
| 7.
Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study
JMIR AI 2024;3(1):e60020
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| 1205 | 0 | 37 | |
| 8.
Toward Clinical Generative AI: Conceptual Framework
JMIR AI 2024;3(1):e55957
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| 1253 | 7 | 36 | |
| 9.
Evaluating Literature Reviews Conducted by Humans Versus ChatGPT: Comparative Study
JMIR AI 2024;3(1):e56537
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| 1482 | 8 | 35 | |
| 10.
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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| 1686 | 1 | 30 | |
| 11.
Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study
JMIR AI 2025;4(1):e60847
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| 811 | 0 | 28 | |
| 12.
Role of Ethics in Developing AI-Based Applications in Medicine: Insights From Expert Interviews and Discussion of Implications
JMIR AI 2024;3(1):e51204
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| 773 | 4 | 26 | |
| 13.
Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial
JMIR AI 2024;3(1):e52615
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| 1039 | 31 | 25 | |
| 14.
A Comparison of Personalized and Generalized Approaches to Emotion Recognition Using Consumer Wearable Devices: Machine Learning Study
JMIR AI 2024;3(1):e52171
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| 673 | 2 | 24 | |
| 15.
Regulatory Frameworks for AI-Enabled Medical Device Software in China: Comparative Analysis and Review of Implications for Global Manufacturer
JMIR AI 2024;3(1):e46871
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| 745 | 0 | 24 | |
| 16.
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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| 1174 | 15 | 23 | |
| 17.
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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| 1292 | 8 | 23 | |
| 18.
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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| 940 | 2 | 23 | |
| 19.
Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability Framework for Safe and Effective Large Language Models in Medical Education: Narrative Review and Qualitative Study
JMIR AI 2024;3(1):e51834
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| 624 | 3 | 22 | |
| 20.
The Utility and Implications of Ambient Scribes in Primary Care
JMIR AI 2024;3(1):e57673
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| 828 | 0 | 22 | |
| 21.
Self-Supervised Electroencephalogram Representation Learning for Automatic Sleep Staging: Model Development and Evaluation Study
JMIR AI 2023;2(1):e46769
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| 675 | 3 | 22 | |
| 22.
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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| 1099 | 9 | 21 | |
| 23.
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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| 2212 | 4 | 21 | |
| 24.
Can Large Language Models Replace Therapists? Evaluating Performance at Simple Cognitive Behavioral Therapy Tasks
JMIR AI 2024;3(1):e52500
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| 631 | 10 | 20 | |
| 25.
Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study
JMIR AI 2024;3(1):e52095
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| 755 | 11 | 20 | |