{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T09:36:22Z","timestamp":1777973782778,"version":"3.51.4"},"reference-count":66,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T00:00:00Z","timestamp":1738195200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:p>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\u2019s 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\u2013from 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.<\/jats:p>","DOI":"10.3389\/frai.2025.1518049","type":"journal-article","created":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T06:25:52Z","timestamp":1738218352000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":53,"title":["Benefits, limits, and risks of ChatGPT in medicine"],"prefix":"10.3389","volume":"8","author":[{"given":"Jonathan A.","family":"Tangsrivimol","sequence":"first","affiliation":[]},{"given":"Erfan","family":"Darzidehkalani","sequence":"additional","affiliation":[]},{"given":"Hafeez Ul Hassan","family":"Virk","sequence":"additional","affiliation":[]},{"given":"Zhen","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Jan","family":"Egger","sequence":"additional","affiliation":[]},{"given":"Michelle","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Sean","family":"Hacking","sequence":"additional","affiliation":[]},{"given":"Benjamin S.","family":"Glicksberg","sequence":"additional","affiliation":[]},{"given":"Markus","family":"Strauss","sequence":"additional","affiliation":[]},{"given":"Chayakrit","family":"Krittanawong","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2025,1,30]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"109729","DOI":"10.1016\/j.resuscitation.2023.109729","article-title":"Exploring ChatGPT for information of cardiopulmonary resuscitation","volume":"185","author":"Ahn","year":"2023","journal-title":"Resuscitation"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"e179","DOI":"10.1016\/S2589-7500(23)00048-1","article-title":"Using ChatGPT to write patient clinic letters","volume":"5","author":"Ali","year":"2023","journal-title":"Lancet Digit Health"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"e35179","DOI":"10.7759\/cureus.35179","article-title":"Artificial hallucinations in ChatGPT: implications in scientific writing","volume":"15","author":"Alkaissi","year":"2023","journal-title":"Cureus"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1056\/CAT.23.0043","article-title":"An interview with ChatGPT about health care","volume":"4","author":"Asch","year":"2023","journal-title":"Catalyst Nonissue Content"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.ajem.2023.03.027","article-title":"ChatGPT: the next-gen tool for triaging?","volume":"69","author":"Bhattaram","year":"2023","journal-title":"Am. 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