ChatGPT: A Conceptual Review of Applications and Utility in the Field of Medicine.

Shiavax J Rao, Benjamin S Glicksberg, Ameesh Isath, Hafeez Ul Hassan Virk, Chayakrit Krittanawong, Zhen Wang, Parvathy Krishnan, Jonathan A Tangsrivimol

Journal: Journal of medical systems 2024;48(1):59

PMID: 38836893

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Abstract

Artificial Intelligence, specifically advanced language models such as ChatGPT, have the potential to revolutionize various aspects of healthcare, medical education, and research. In this narrative review, we evaluate the myriad applications of ChatGPT in diverse healthcare domains. We discuss its potential role in clinical decision-making, exploring how it can assist physicians by providing rapid, data-driven insights for diagnosis and treatment. We review the benefits of ChatGPT in personalized patient care, particularly in geriatric care, medication management, weight loss and nutrition, and physical activity guidance. We further delve into its potential to enhance medical research, through the analysis of large datasets, and the development of novel methodologies. In the realm of medical education, we investigate the utility of ChatGPT as an information retrieval tool and personalized learning resource for medical students and professionals. There are numerous promising applications of ChatGPT that will likely induce paradigm shifts in healthcare practice, education, and research. The use of ChatGPT may come with several benefits in areas such as clinical decision making, geriatric care, medication management, weight loss and nutrition, physical fitness, scientific research, and medical education. Nevertheless, it is important to note that issues surrounding ethics, data privacy, transparency, inaccuracy, and inadequacy persist. Prior to widespread use in medicine, it is imperative to objectively evaluate the impact of ChatGPT in a real-world setting using a risk-based approach.

Address: Department of Medicine, MedStar Union Memorial Hospital, Baltimore, MD, USA.; Department of Cardiology, Westchester Medical Center and New York Medical College, Valhalla, NY, USA.; Department of Pediatrics, Westchester Medical Center and New York Medical College, Valhalla, NY, USA.; Division of Neurosurgery, Department of Surgery, Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, 10210, Thailand.; Department of Neurological Surgery, Weill Cornell Medicine Brain and Spine Center, New York, NY, 10022, USA.; Harrington Heart & Vascular Institute, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.; Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.; Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.; Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Cardiology Division, NYU Langone Health and NYU School of Medicine, 550 First Avenue, New York, NY, 10016, USA. [email protected].

DOI: 10.1007/s10916-024-02075-x

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https://dx.doi.org/10.1007/s10916-024-02075-x

MeSH Terms: Humans, Artificial Intelligence, Clinical Decision-Making, Precision Medicine, Education, Medical