Jonathan A Tangsrivimol ¹ Erfan Darzidehkalani ² Hafeez Ul Hassan Virk ³ Zhen Wang ^4,5 Jan Egger ⁶ Michelle Wang ⁷ Sean Hacking ⁸ Benjamin S Glicksberg ⁹ Markus Strauss ^10* Chayakrit Krittanawong ¹¹

• ¹ Weill Cornell Medicine, Cornell University, New York, New York, United States
• ² Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
• ³ Harrington Heart and Vascular Institute, University Hospitals of Cleveland, Cleveland, Ohio, United States
• ⁴ Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Jacksonville, Florida, United States
• ⁵ Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, Michigan, United States
• ⁶ Essen University Hospital, Essen, North Rhine-Westphalia, Germany
• ⁷ Bakar Computational Health Sciences Institute, Medical Center, University of California, San Francisco, San Francisco, California, United States
• ⁸ Department of Pathology, Grossman School of Medicine, New York University, New York, New York, United States
• ⁹ Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, United States
• ¹⁰ Department of Cardiology I, University Hospital Münster, Münster, North Rhine-Westphalia, Germany
• ¹¹ Langone Medical Center, New York University, New York City, New York, United States

ChatGPT represents a transformative technology in healthcare, with demonstrated impacts across clinical practice, medical education, and research. Studies show significant efficiency gains, including 70% reduction in administrative time for discharge summaries and achievement of medical professional-level performance on standardized tests (60% accuracy on USMLE, 78.2% on PubMedQA). ChatGPT offers personalized learning platforms, automated scoring, and instant access to vast medical knowledge in medical education, addressing resource limitations and enhancing training efficiency. It streamlines clinical workflows by supporting triage processes, generating discharge summaries, and alleviating administrative burdens, allowing healthcare professionals to focus more on patient care. Additionally, ChatGPT facilitates remote monitoring and chronic disease management, providing personalized advice, medication reminders, and emotional support, thus bridging gaps between clinical visits. Its ability to process and synthesize vast amounts of data accelerates research workflows, aiding in literature reviews, hypothesis generation, and clinical trial designs. This paper aims to gather and analyze published studies involving ChatGPT, focusing on exploring its advantages and disadvantages within the healthcare context. To aid in understanding and progress, our analysis is organized into six key areas: 1) Information and Education, 2) Triage and Symptom Assessment, 3) Remote Monitoring and Support, 4) Mental Healthcare Assistance, 5) Research and Decision Support, and 6) Language Translation. Realizing ChatGPT’s full potential in healthcare requires addressing key limitations, such as its lack of clinical experience, inability to process visual data, and absence of emotional intelligence. Ethical, privacy, and regulatory challenges further complicate its integration. Future improvements should focus on enhancing accuracy, developing multimodal AI models, improving empathy through sentiment analysis, and safeguarding against artificial hallucination. While not a replacement for healthcare professionals, ChatGPT can serve as a powerful assistant, augmenting their expertise to improve efficiency, accessibility, and quality of care. This collaboration ensures responsible adoption of AI in transforming healthcare delivery. While ChatGPT demonstrates significant potential in healthcare transformation, systematic evaluation of its implementation across different healthcare settings reveals varying levels of evidence quality - from robust randomized trials in medical education to preliminary observational studies in clinical practice. This heterogeneity in evidence quality necessitates a structured approach to future research and implementation.