Evaluating artificial intelligence in medicine: phases of clinical research

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Guidelines for Artificial Intelligence in Medicine: Literature Review and Content Analysis of Frameworks

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A Research Ethics Framework for the Clinical Translation of Healthcare Machine Learning

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Implementation frameworks for end-to-end clinical AI: derivation of the SALIENT framework

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Artificial Intelligence for Disease Assessment in Inflammatory Bowel Disease: How Will it Change Our Practice?

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Algorithmovigilance—Advancing methods to analyze and monitor artificial intelligence-driven health care for effectiveness and equity

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Artificial Intelligence–enabled Decision Support in Surgery

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How Clinicians Perceive Artificial Intelligence–Assisted Technologies in Diagnostic Decision Making: Mixed Methods Approach

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Translation of AI into oncology clinical practice

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Informed consent for artificial intelligence in emergency medicine: A practical guide

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FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

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Randomized Controlled Trials in Medical AI

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Artificial Intelligence in Pediatrics: Learning to Walk Together

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Methodology for Conducting Post-Marketing Surveillance of Software as a Medical Device Based on Artificial Intelligence Technologies

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AI Quality Standards in Health Care: Rapid Umbrella Review

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A checklist for reporting, reading and evaluating Artificial Intelligence Technology Enhanced Learning (AITEL) research in medical education

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Healthcare Systems and Artificial Intelligence: Focus on Challenges and the International Regulatory Framework

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Utilizing standardized nursing terminologies in implementing an AI-powered fall-prevention tool to improve patient outcomes: a multihospital study

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Transforming cancer clinical trials: The integral role of artificial intelligence in electronic health records for efficient patient recruitment

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Critical Appraisal of Artificial Intelligence–Enabled Imaging Tools Using the Levels of Evidence System

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Evaluation and Regulation of Artificial Intelligence Medical Devices for Clinical Decision Support

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Ethical implications of using general-purpose LLMs in clinical settings: a comparative analysis of prompt engineering strategies and their impact on patient safety

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Machine learning in cardiac surgery: a narrative review

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Digital Technology: Key considerations for the use of artificial intelligence in healthcare and clinical research

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Healthcare 5.0-Driven Clinical Intelligence: The Learn-Predict-Monitor-Detect-Correct Framework for Systematic Artificial Intelligence Integration in Critical Care

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Artificial intelligence (AI) for neurologists: do digital neurones dream of electric sheep?

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Mindbench.ai: an actionable platform to evaluate the profile and performance of large language models in a mental healthcare context

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Digital public health leadership in the global fight for health security

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Artificial Intelligence in Medical Education

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Bias in Artificial Intelligence

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Physicians’ and Machine Learning Researchers’ Perspectives on Ethical Issues in the Early Development of Clinical Machine Learning Tools: Qualitative Interview Study

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Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial

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A scoping review of silent trials for medical artificial intelligence

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Clinical Needs Assessment of a Machine Learning–Based Asthma Management Tool: User-Centered Design Approach

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Approaches to Sampling for Quality Control of Artificial Intelligence in Biomedical Research

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Advancing Fairness in Cardiac Care: Strategies for Mitigating Bias in Artificial Intelligence Models Within Cardiology

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Pharmacy Futures: Summit on Artificial Intelligence in Pharmacy Practice

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Resolving the Credibility Crisis: Recommendations for Improving Predictive Algorithms for Clinical Utility

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$$D_MD_RDF$$: diabetes mellitus and retinopathy detection framework using artificial intelligence and feature selection

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Validation of an Artificial Intelligence-Powered Virtual Assistant for Emergency Triage in Neurology

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Beyond multiple-choice questions: Rethinking evaluation frameworks for large language models for clinical medicine

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Diagnosing Allergic Contact Dermatitis Using Deep Learning: Single-Arm, Pragmatic Clinical Trial with an Observer Performance Study to Compare Artificial Intelligence Performance with Human Reader Performance

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Augmenting Quality Assurance Measures in Treatment Review with Machine Learning in Radiation Oncology

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From Code to Clinic: A Phase-based Framework for AI Research in Healthcare (P1-15.004)

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Clinical trials informed framework for real world clinical implementation and deployment of artificial intelligence applications

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Clinical Evaluation of Artificial Intelligence-Enabled Interventions

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How artificial intelligence is disrupting the field of medical knowledge and evaluation: a narrative review

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