Benefits, limits, and risks of ChatGPT in medicine
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...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Artificial Intelligence |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2025.1518049/full |
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| author | Jonathan A. Tangsrivimol Jonathan A. Tangsrivimol Erfan Darzidehkalani Hafeez Ul Hassan Virk Zhen Wang Zhen Wang Jan Egger Michelle Wang Sean Hacking Benjamin S. Glicksberg Markus Strauss Markus Strauss Chayakrit Krittanawong Chayakrit Krittanawong |
| author_facet | Jonathan A. Tangsrivimol Jonathan A. Tangsrivimol Erfan Darzidehkalani Hafeez Ul Hassan Virk Zhen Wang Zhen Wang Jan Egger Michelle Wang Sean Hacking Benjamin S. Glicksberg Markus Strauss Markus Strauss Chayakrit Krittanawong Chayakrit Krittanawong |
| author_sort | Jonathan A. Tangsrivimol |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-da20adfffcfc47fa861e85b27e0b0439 |
| institution | Kabale University |
| issn | 2624-8212 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj-art-da20adfffcfc47fa861e85b27e0b04392025-01-30T06:22:47ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122025-01-01810.3389/frai.2025.15180491518049Benefits, limits, and risks of ChatGPT in medicineJonathan A. Tangsrivimol0Jonathan A. Tangsrivimol1Erfan Darzidehkalani2Hafeez Ul Hassan Virk3Zhen Wang4Zhen Wang5Jan Egger6Michelle Wang7Sean Hacking8Benjamin S. Glicksberg9Markus Strauss10Markus Strauss11Chayakrit Krittanawong12Chayakrit Krittanawong13Department of Neurosurgery, and Neuroscience, Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, NY, United StatesDepartment of Neurosurgery, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, ThailandMIT Computer Science & Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United StatesHarrington Heart & Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH, United StatesRobert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United StatesDivision of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United StatesInstitute for Artificial Intelligence in Medicine, University Hospital Essen (AöR), Essen, GermanyBakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, United StatesDepartment of Pathology, NYU Grossman School of Medicine, New York, NY, United States0Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States1Department of Cardiology I, Coronary and Peripheral Vascular Disease, Heart Failure Medicine, University Hospital Muenster, Muenster, Germany2Department of Cardiology, Sector Preventive Medicine, Health Promotion, Faculty of Health, School of Medicine, University Witten/Herdecke, Hagen, Germany3Cardiology Division, New York University Langone Health, New York University School of Medicine, New York, NY, United States4HumanX, Delaware, DE, United StatesChatGPT 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.https://www.frontiersin.org/articles/10.3389/frai.2025.1518049/fulllarge language modelsdeep learningartificial intelligenceChatGPThealthcare questionshealthcare |
| spellingShingle | Jonathan A. Tangsrivimol Jonathan A. Tangsrivimol Erfan Darzidehkalani Hafeez Ul Hassan Virk Zhen Wang Zhen Wang Jan Egger Michelle Wang Sean Hacking Benjamin S. Glicksberg Markus Strauss Markus Strauss Chayakrit Krittanawong Chayakrit Krittanawong Benefits, limits, and risks of ChatGPT in medicine Frontiers in Artificial Intelligence large language models deep learning artificial intelligence ChatGPT healthcare questions healthcare |
| title | Benefits, limits, and risks of ChatGPT in medicine |
| title_full | Benefits, limits, and risks of ChatGPT in medicine |
| title_fullStr | Benefits, limits, and risks of ChatGPT in medicine |
| title_full_unstemmed | Benefits, limits, and risks of ChatGPT in medicine |
| title_short | Benefits, limits, and risks of ChatGPT in medicine |
| title_sort | benefits limits and risks of chatgpt in medicine |
| topic | large language models deep learning artificial intelligence ChatGPT healthcare questions healthcare |
| url | https://www.frontiersin.org/articles/10.3389/frai.2025.1518049/full |
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