The DOI matches its Crossref record; 17 of the 18 references it cites were found in a registry or an index, and 1 are not checked yet.
Using ChatGPT in Medical Research: Current Status and Future Directions
Open accessAbstract
Objective: This review aims to evaluate the current evidence on the use of the Generative Pre-trained Transformer (ChatGPT) in medical research, including but not limited to treatment, diagnosis, or medication provision. Methods: This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched Google Scholar, Web of Science, PubMed, and Medline to identify studies published between 2022 and 2023 that aimed to utilize ChatGPT in medical research. All identified references were stored in EndNote. Results: We initially identified 114 articles, out of which six studies met the inclusion and exclusion criteria for full-text screening. Among the six studies, two focused on drug development (33.33%), two on literature review writing (33.33%), and one each on medical report improvement, provision of medical information, improving research conduct, data analysis, and personalized medicine (16.67% each). Conclusion: ChatGPT has the potential to revolutionize medical research in various ways. However, its accuracy, originality, academic integrity, and ethical issues must be thoroughly discussed and improved before its widespread implementation in clinical research and medical practice.
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“As part of this investigation, a systematic literature review was conducted using the PRISMA methodology (Supplementary Materials) [40,45,46,47,48,49,50].”
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“The integration of ChatGPT into medical practices and healthcare settings presents challenges and ethical considerations.”
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“Ethical concerns arise when content generated by AI is mistaken for the expertise of a human.”
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“One challenge is that the responses of ChatGPT are based on the data on which it was trained, which may result in biased or inaccurate information.”
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Cites
The potential for artificial intelligence in healthcare
Davenport, T., & Kalakota, R. (2019) · Future Healthcare Journal · doi:10.7861/futurehosp.6-2-94 · Cited by 3,800
Reprint—Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & and the PRISMA Group (2009) · Physical Therapy · doi:10.1093/ptj/89.9.873 · Cited by 2,486
Artificial intelligence in drug development: Present status and future prospects
Mak, K.-K., & Pichika, M. R. (2019) · Drug Discovery Today · doi:10.1016/j.drudis.2018.11.014 · Cited by 1,018
The role of AI in drug discovery: challenges, opportunities, and strategies
Blanco-González, A., Cabezón, A., Seco-González, A., Conde-Torres, D., Antelo-Riveiro, P., Piñeiro, Á., & Garcia-Fandino, R. (2023) · Pharmaceuticals · doi:10.3390/ph16060891 · Cited by 690
The benefits and challenges of chatgpt: An overview
Deng, J., & Lin, Y. (2023) · Frontiers in Computing and Intelligent Systems · doi:10.54097/fcis.v2i2.4465 · Cited by 611
ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports
Jeblick, K., Schachtner, B., Dexl, J., Mittermeier, A., Stüber, A. T., Topalis, J., Weber, T., Wesp, P., Sabel, B. O., Ricke, J., et al. (2023) · European Radiology · doi:10.1007/s00330-023-10213-1 · Cited by 549
OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare
Aydın, Ö., & Karaarslan, E. (2022) · doi:10.2139/ssrn.4308687 · Cited by 391
The Future of AI in Medicine: A Perspective from a Chatbot
King, M. R. (2023) · Annals of Biomedical Engineering · doi:10.1007/s10439-022-03121-w · Cited by 299
Secure Artificial Intelligence of Things for Implicit Group Recommendations
Yu, K., Guo, Z., Shen, Y., Wang, W. W., Lin, J. C., & Sato, T. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3079574 · Cited by 197
The emerging roles of artificial intelligence in cancer drug development and precision therapy
Liang, G., Fan, W., Luo, H., & Zhu, X. M. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.110255 · Cited by 149
A conversation with ChatGPT on the role of computational systems biology in stem cell research
Cahan, P., & Treutlein, B. (2023) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.12.009 · Cited by 125
ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study on Simplified Radiology Reports
Jeblick, K., Schachtner, B., Dexl, J., Mittermeier, A., Stüber, A. T., Topalis, J., Weber, T., Wesp, P., Sabel, B., Ricke, J., et al. (2022) · arXiv · doi:10.48550/arxiv.2212.14882 · Cited by 97
Artificial Intelligence Discusses the Role of Artificial Intelligence in Translational Medicine
Mann, D. L. (2023) · JACC: Basic to Translational Science · doi:10.1016/j.jacbts.2023.01.001 · Cited by 93
Can ChatGPT Write a Good Boolean Query for Systematic Review Literature Search?
Wang, S., Scells, H., Koopman, B., & Zuccon, G. (2023) · arXiv · doi:10.48550/arxiv.2302.03495 · Cited by 40
Machine learning-based patient classification system for adults with stroke: A systematic review
Ruksakulpiwat, S., Thongking, W., Zhou, W., Benjasirisan, C., Phianhasin, L., Schiltz, N. K., & Brahmbhatt, S. (2021) · Chronic Illness · doi:10.1177/17423953211067435 · Cited by 16
Self-citationArtificial Intelligence for Quality Improvement in Radiology
Loehfelm, T. W. (2021) · Radiologic Clinics of North America · doi:10.1016/j.rcl.2021.07.005 · Cited by 7
The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies
Blanco-Gonzalez, A., Cabezon, A., Seco-Gonzalez, A., et al. (2022) · arXiv · doi:10.48550/arxiv.2212.08104
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Cited by
Sorted by citations
The application of large language models in medicine: A scoping review
Meng, X., Yan, X., Zhang, K., Liu, D., Cui, X., Yang, Y., Zhang, M., Cao, C., Wang, J., Wang, X., et al. (2024) · iScience · doi:10.1016/j.isci.2024.109713 · Cited by 414
Generative AI Literacy: Twelve Defining Competencies
Annapureddy, R., Fornaroli, A., & Gatica-Perez, D. (2025) · Digital Government: Research and Practice · doi:10.1145/3685680 · Cited by 333
Higher education students’ perceptions of ChatGPT: A global study of early reactions
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Younis, H. A., Eisa, T. A. E., Nasser, M., Sahib, T. M., Noor, A. A., Alyasiri, O. M., Salisu, S., Hayder, I. M., & Younis, H. A. (2024) · Diagnostics · doi:10.3390/diagnostics14010109 · Cited by 242
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Metadata
- Authors
- Ruksakulpiwat, S., Kumar, A., & Ajibade, A.
- Affiliations
- Mahidol University (TH)
- Case Western Reserve University (US)
- Corresponding author
- Ruksakulpiwat, Suebsarn
- Venue
- Journal of Multidisciplinary Healthcare
- Publisher
- Informa UK Limited
- Published
- 2023-05
- Volume
- Volume 16
- Pages
- 1513-1520
- ISSN
- 1178-2390 (ISSN-L)
- PMC
- PMC10239248
- OpenAlex
- W4379376212
- Cited by
- 156
- References
- 17
- Citations by year
- 2026: 10 · 2025: 36 · 2024: 79 · 2023: 31
- FWCI
- 6.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Multidisciplinary Healthcare (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Dove Medical Press (Taylor and Francis Group) (submittedVersion, cc-by-nc)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- ChatGPT, large language models, medical research, drug development, literature review writing, personalized medicine, research ethics, academic integrity, artificial intelligence in healthcare
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