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Using Conversational AI to Facilitate Mental Health Assessments and Improve Clinical Efficiency Within Psychotherapy Services: Real-World Observational Study

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Adolescents’ Well-being While Using a Mobile Artificial Intelligence–Powered Acceptance Commitment Therapy Tool: Evidence From a Longitudinal Study

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Strategies to Improve the Impact of Artificial Intelligence on Health Equity: Scoping Review

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Predicting Treatment Interruption Among People Living With HIV in Nigeria: Machine Learning Approach

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The Application of Artificial Intelligence in Health Care Resource Allocation Before and During the COVID-19 Pandemic: Scoping Review

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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

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Comparing the Efficacy and Efficiency of Human and Generative AI: Qualitative Thematic Analyses

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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

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How Explainable Artificial Intelligence Can Increase or Decrease Clinicians’ Trust in AI Applications in Health Care: Systematic Review

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Evaluating the Diagnostic Performance of Symptom Checkers: Clinical Vignette Study

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Toward Clinical Generative AI: Conceptual Framework

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Application of Artificial Intelligence to the Monitoring of Medication Adherence for Tuberculosis Treatment in Africa: Algorithm Development and Validation

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Impact of a Digital Scribe System on Clinical Documentation Time and Quality: Usability Study

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Evaluating Literature Reviews Conducted by Humans Versus ChatGPT: Comparative Study

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Artificial Intelligence–Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study

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Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study

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Artificial Intelligence in Health Care—Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study

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A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach

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Generating Synthetic Electronic Health Record Data Using Generative Adversarial Networks: Tutorial

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Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning–Based Natural Language Processing

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