The Emerging Role of Generative Artificial Intelligence in Medical Education, Research, and Practice
Open accessAbstract
Recent breakthroughs in generative artificial intelligence (GAI) and the emergence of transformer-based large language models such as Chat Generative Pre-trained Transformer (ChatGPT) have the potential to transform healthcare education, research, and clinical practice. This article examines the current trends in using GAI models in medicine, outlining their strengths and limitations. It is imperative to develop further consensus-based guidelines to govern the appropriate use of GAI, not only in medical education but also in research, scholarship, and clinical practice.
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There is literature evidence for the potentially negative impact of ChatGPT on students' learning skills, particularly when the tool is used to generate essays or assignments that students submit without fully engaging in the educational process.
“There is already literature evidence for the potentially negative impact of ChatGPT on students' learning skills, particularly when the tool is used to generate essays or assignments that students submit without fully engaging in the educational process [28].”
From Health profession students' perceptions of ChatGPT in healthcare and education: insights from a mixed-methods study (2025) · cites this paper as [28]
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- Authors
- Shoja, M. M., Van de Ridder, J. M. M., & Rajput, V.
- Affiliations
- Nova Southeastern University (US)
- Corresponding author
- Shoja, Mohammadali M
- Venue
- Cureus
- Published
- 2023-06-24
- Volume
- 15
- Issue
- 6
- Pages
- e40883-e40883
- ISSN
- 2168-8184 (ISSN-L)
- PMC
- PMC10363933
- OpenAlex
- W4381997112
- Cited by
- 69
- References
- 29
- Citations by year
- 2026: 11 · 2025: 23 · 2024: 28 · 2023: 7
- FWCI
- 0.81
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Cureus (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- NSUWorks (Nova Southeastern University) (submittedVersion, cc-by)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- generative AI, large language models, ChatGPT, medical education, medical research, clinical practice, AI guidelines, transformer models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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