The application of large language models in medicine: A scoping review

Scoping studies: advancing the methodology

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Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q. V., & Zhou, D. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-1800 · Cited by 4,505 · see citing works

Training language models to follow instructions with human feedback

Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C. L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al. (2022) · arXiv · doi:10.48550/arxiv.2203.02155 · Cited by 4,208 · see citing works

Large language models encode clinical knowledge

Singhal, K., Azizi, S., Tu, T., Mahdavi, S. S., Wei, J., Chung, H. W., Scales, N., Tanwani, A., Cole-Lewis, H., Pfohl, S., et al. (2023) · Nature · doi:10.1038/s41586-023-06291-2 · Cited by 4,083 · see citing works

Large language models in medicine

Thirunavukarasu, A. J., Ting, D. S. J., Elangovan, K., Gutierrez, L., Tan, T. F., & Ting, D. S. W. (2023) · Nature Medicine · doi:10.1038/s41591-023-02448-8 · Cited by 3,944 · see citing works

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., Badreldin, H. A., et al. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04698-z · Cited by 3,146 · see citing works

Training Language Models to Follow Instructions with Human Feedback

Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-2011 · Cited by 3,117 · see citing works

A Survey of Large Language Models

Zhao, W. X., Zhou, K., Li, J., Tang, T., Dong, Z., Hou, Y., Zhang, B., Min, Y., Zhang, J., Liu, P., et al. (2026) · Frontiers of Computer Science · doi:10.1007/s11704-026-60308-3 · Cited by 2,093 · see citing works

A Survey of Large Language Models

Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., et al. (2023) · arXiv · doi:10.48550/arxiv.2303.18223 · Cited by 2,090

Emergent Abilities of Large Language Models

Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., Metzler, D., et al. (2022) · arXiv · doi:10.48550/arxiv.2206.07682 · Cited by 1,264 · see citing works

A Comprehensive Overview of Large Language Models

Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., Akhtar, N., Barnes, N., & Mian, A. (2023) · arXiv · doi:10.48550/arxiv.2307.06435 · Cited by 1,259 · see citing works

A Comprehensive Overview of Large Language Models

Naveed, H., Khan, A. U., Qiu, S., Saqib, M., Anwar, S., Usman, M., Akhtar, N., Barnes, N., & Mian, A. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3744746 · Cited by 1,257 · see citing works

ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations

Dave, T., Athaluri, S. A., & Singh, S. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1169595 · Cited by 1,204 · see citing works

BioGPT: generative pre-trained transformer for biomedical text generation and mining

Luo, R., Sun, L., Xia, Y., Qin, T., Zhang, S., Poon, H., & Liu, T.-Y. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac409 · Cited by 1,150 · see citing works

Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios

Cascella, M., Montomoli, J., Bellini, V., & Bignami, E. (2023) · Journal of Medical Systems · doi:10.1007/s10916-023-01925-4 · Cited by 1,120 · see citing works

A large language model for electronic health records

Yang, X., Chen, A., PourNejatian, N., Shin, H. C., Smith, K. E., Parisien, C., Compas, C., Martin, C., Costa, A. B., Flores, M. G., et al. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00742-2 · Cited by 847 · see citing works

Structured information extraction from scientific text with large language models

Dagdelen, J., Dunn, A., Lee, S., Walker, N., Rosen, A. S., Ceder, G., Persson, K. A., & Jain, A. (2024) · Nature Communications · doi:10.1038/s41467-024-45563-x · Cited by 771 · see citing works

ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health

De Angelis, L., Baglivo, F., Arzilli, G., Privitera, G. P., Ferragina, P., Tozzi, A. E., & Rizzo, C. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1166120 · Cited by 708 · see citing works

Harnessing the power of llms in practice: a survey on chatGPT and beyond

Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Zhong, S., Yin, B., & Hu, X. (2024) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3649506 · Cited by 644 · see citing works

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Yin, B., & Hu, X. (2023) · arXiv · doi:10.48550/arxiv.2304.13712 · Cited by 644 · see citing works

Multimodal Neural Language Models

Kiros, R., Salakhutdinov, R., & Zemel, R. (2014) · Cited by 593 · see citing works

PaLM-E: An Embodied Multimodal Language Model

Driess, D., Xia, F., Sajjadi, M. S. M., Lynch, C., Chowdhery, A., Ichter, B., Wahid, A., Tompson, J., Vuong, Q., Yu, T., et al. (2023) · arXiv · doi:10.48550/arxiv.2303.03378 · Cited by 591 · see citing works

Large language models in healthcare and medical domain: A reviewPreprint

Nazi, Z. A., & Peng, W. (2023) · Informatics · doi:10.48550/arxiv.2401.06775 · Cited by 551 · see citing works

Emergency department triage prediction of clinical outcomes using machine learning models

Raita, Y., Goto, T., Faridi, M. K., Brown, D., Camargo, C. A., & Hasegawa, K. (2019) · Critical Care · doi:10.1186/s13054-019-2351-7 · Cited by 531 · see citing works

Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine

Harrer, S. (2023) · eBioMedicine · doi:10.1016/j.ebiom.2023.104512 · Cited by 480 · see citing works

Artificial intelligence in clinical and genomic diagnostics

Dias, R., & Torkamani, A. (2019) · Genome Medicine · doi:10.1186/s13073-019-0689-8 · Cited by 474 · see citing works

Health system-scale language models are all-purpose prediction engines

Jiang, L. Y., Liu, X. C., Nejatian, N. P., Nasir-Moin, M., Wang, D., Abidin, A., Eaton, K., Riina, H. A., Laufer, I., Punjabi, P., et al. (2023) · Nature · doi:10.1038/s41586-023-06160-y · Cited by 460 · see citing works

Accuracy of a Generative Artificial Intelligence Model in a Complex Diagnostic Challenge

Kanjee, Z., Crowe, B., & Rodman, A. (2023) · JAMA · doi:10.1001/jama.2023.8288 · Cited by 449 · see citing works

Creation and Adoption of Large Language Models in Medicine

Shah, N. H., Entwistle, D., & Pfeffer, M. A. (2023) · JAMA · doi:10.1001/jama.2023.14217 · Cited by 435 · see citing works

ToolQA: A Dataset for LLM Question Answering with External ToolsPreprint

Zhuang, Y.-C., Yu, Y., Wang, K., et al. (2023) · Neural Information Processing Systems · doi:10.48550/arxiv.2306.13304 · Cited by 421 · see citing works

Large language models propagate race-based medicine

Omiye, J. A., Lester, J. C., Spichak, S., Rotemberg, V., & Daneshjou, R. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00939-z · Cited by 417 · see citing works

Large language models in healthcare and medical domain: A review

Nazi, Z. A., & Peng, W. (2024) · Informatics · doi:10.3390/informatics11030057 · Cited by 415 · see citing works

Generative AI in Medicine and Healthcare: Promises, Opportunities and Challenges

Zhang, P., & Kamel Boulos, M. N. (2023) · Future Internet · doi:10.3390/fi15090286 · Cited by 411 · cited 1× · see citing works

A study of generative large language model for medical research and healthcare

Peng, C., Yang, X., Chen, A., Smith, K. E., PourNejatian, N., Costa, A. B., Martin, C., Flores, M. G., Zhang, Y., Magoc, T., et al. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00958-w · Cited by 408 · see citing works

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms: A Scoping Review

Daneshjou, R., Smith, M. P., Sun, M. D., Rotemberg, V., & Zou, J. (2021) · JAMA Dermatology · doi:10.1001/jamadermatol.2021.3129 · Cited by 403 · see citing works

Using ChatGPT to write patient clinic letters

Ali, S. R., Dobbs, T. D., Hutchings, H. A., & Whitaker, I. S. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00048-1 · Cited by 375 · see citing works

Social Media– and Internet-Based Disease Surveillance for Public Health

Aiello, A. E., Renson, A., & Zivich, P. N. (2020) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-040119-094402 · Cited by 363 · see citing works

Leveraging large language models for decision support in personalized oncology

Benary, M., Wang, X. D., Schmidt, M., Soll, D., Hilfenhaus, G., Nassir, M., Sigler, C., Knödler, M., Keller, U., Beule, D., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.43689 · Cited by 306 · see citing works

Artificial intelligence in healthcare: Complementing, not replacing, doctors and healthcare providers

Sezgın, E. (2023) · Digital Health · doi:10.1177/20552076231186520 · Cited by 279 · see citing works

Considering the possibilities and pitfalls of Generative Pre-trained Transformer 3 (GPT-3) in healthcare delivery

Korngiebel, D. M., & Mooney, S. D. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00464-x · Cited by 259 · see citing works

Comparison of Ophthalmologist and Large Language Model Chatbot Responses to Online Patient Eye Care Questions

Bernstein, I. A., Zhang, Y., Govil, D., Majid, I., Chang, R. T., Sun, Y., Shue, A., Chou, J. C., Schehlein, E. M., Christopher, K. L., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.30320 · Cited by 250 · see citing works

Benchmarking large language models for biomedical natural language processing applications and recommendations

Chen, Q., Hu, Y., Peng, X., Xie, Q., Jin, Q., Gilson, A., Singer, M. B., Ai, X., Lai, P.-T., Wang, Z., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56989-2 · Cited by 219 · see citing works

Are ChatGPT and large language models “the answer” to bringing us closer to systematic review automation?

Qureshı, R., Shaughnessy, D. P., Gill, K., Robinson, K. A., Li, T., & Agai, E. (2023) · Systematic Reviews · doi:10.1186/s13643-023-02243-z · Cited by 217 · see citing works

Will ChatGPT transform healthcare?

(2023) · Nature Medicine · doi:10.1038/s41591-023-02289-5 · Cited by 214 · see citing works

Large language model AI chatbots require approval as medical devices

Gilbert, S., Harvey, H., Melvin, T., Vollebregt, E., & Wicks, P. (2023) · Nature Medicine · doi:10.1038/s41591-023-02412-6 · Cited by 207 · see citing works

Eight Things to Know about Large Language Models

Bowman, S. R. (2024) · Critical AI · doi:10.1215/2834703x-11556011 · Cited by 198 · see citing works

Large language model-based chatbot vs surgeon-generated informed consent documentation for common procedures

Decker, H., Trang, K., Ramirez, J., Colley, A., Pierce, L., Coleman, M., Bongiovanni, T., Melton, G. B., & Wick, E. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.36997 · Cited by 178 · see citing works

The Challenges for Regulating Medical Use of ChatGPT and Other Large Language Models

Minssen, T., Vayena, E., & Cohen, I. G. (2023) · JAMA · doi:10.1001/jama.2023.9651 · Cited by 171 · see citing works

Using ChatGPT in Medical Research: Current Status and Future Directions

Ruksakulpiwat, S., Kumar, A., & Ajibade, A. (2023) · Journal of Multidisciplinary Healthcare · doi:10.2147/jmdh.s413470 · Cited by 156 · see citing works

The promise of large language models in health care

Arora, A., & Arora, A. (2023) · The Lancet · doi:10.1016/s0140-6736(23)00216-7 · Cited by 153 · see citing works

Eight Things to Know about Large Language Models

Bowman, S. R. (2023) · arXiv · doi:10.48550/arxiv.2304.00612 · Cited by 137 · cited 2× · see citing works

Flexible electronics for cardiovascular healthcare monitoring

Zhang, T., Liu, N., Xu, J., Liu, Z., Zhou, Y., Yang, Y., Li, S., Huang, Y., & Jiang, S. (2023) · The Innovation · doi:10.1016/j.xinn.2023.100485 · Cited by 128 · see citing works

Ins and outs of AlphaFold2 transmembrane protein structure predictions

Hegedűs, T., Geisler, M., Lukács, G. L., & Farkas, B. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-021-04112-1 · Cited by 127 · see citing works

ChatGPT has entered the classroom: how LLMs could transform education

Extance, A. (2023) · Nature · doi:10.1038/d41586-023-03507-3 · Cited by 127 · see citing works

ChatGPT outscored human candidates in a virtual objective structured clinical examination in obstetrics and gynecology

Li, S. W. L., Kemp, M. W., Logan, S. J. S., Dimri, P. S., Singh, N., Mattar, C. N. Z., Dashraath, P., Ramlal, H., Mahyuddin, A. P., Kanayan, S., et al. (2023) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2023.04.020 · Cited by 117 · see citing works

Artificial intelligence in health‐care: implications for the job design of healthcare professionals

Tursunbayeva, A., & Renkema, M. (2022) · Asia Pacific Journal of Human Resources · doi:10.1111/1744-7941.12325 · Cited by 116 · see citing works

Evaluating Artificial Intelligence Responses to Public Health Questions

Ayers, J. W., Zhu, Z., Poliak, A., Leas, E. C., Dredze, M. H., Hogarth, M. A., & Smith, D. M. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.17517 · Cited by 115 · see citing works

Mitigating bias in artificial intelligence: Fair data generation via causal models for transparent and explainable decision-making

González-Sendino, R., Serrano, E., & Bajo, J. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.02.023 · Cited by 111 · see citing works

ChatGPT, Bard, and large language models for biomedical research: opportunities and pitfalls

Thapa, S., & Adhikari, S. (2023) · Annals of Biomedical Engineering · doi:10.1007/s10439-023-03284-0 · Cited by 111 · see citing works

Use of ChatGPT: What does it mean for biology and environmental science?

Agathokleous, E., Saitanis, C. J., Fang, C., & Yu, Z. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.164154 · Cited by 105 · see citing works

HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)

Ali, T., Kostakos, P., & Sheikhi, S. (2026) · Telecom · doi:10.3390/telecom7030073 · Cited by 104 · see citing works

How Chatbots and Large Language Model Artificial Intelligence Systems Will Reshape Modern Medicine: Fountain of Creativity or Pandora’s Box?

Li, R., Kumar, A., & Chen, J. H. (2023) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2023.1835 · Cited by 104 · see citing works

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 · see citing works

MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning TasksPreprint

Zhang, L., Zhang, Y., Ren, K., et al. (2023) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.48550/arxiv.2304.14979 · Cited by 91 · see citing works

LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?Preprint

Glukhov, D., Shumailov, I., Gal, Y., Papernot, N., & Papyan, V. (2023) · arXiv.org · doi:10.48550/arxiv.2307.10719 · Cited by 89 · see citing works

ToolQA: A Dataset for LLM Question Answering with External Tools

Zhuang, Y., Yu, Y., Wang, K., Sun, H., & Zhang, C. (2023) · neural information processing systems · doi:10.52202/075280-2180 · Cited by 73 · see citing works

Large Language Models Answer Medical Questions Accurately, but Can’t Match Clinicians’ Knowledge

Harris, E. (2023) · JAMA · doi:10.1001/jama.2023.14311 · Cited by 70 · see citing works

ChatGPT—A promising generative AI tool and its implications for cancer care

Uprety, D., Zhu, D., & West, H. (. (2023) · Cancer · doi:10.1002/cncr.34827 · Cited by 68 · see citing works

Structured information extraction from complex scientific text with fine-tuned large language models

Dunn, A., Dagdelen, J., Walker, N., Lee, S., Rosen, A. S., Ceder, G., Persson, K., & Jain, A. (2022) · arXiv · doi:10.48550/arxiv.2212.05238 · Cited by 67 · see citing works

Is ChatGPT an Evidence-based Doctor?

Zhou, Z., Wang, X., Li, X., & Liao, L. (2023) · European Urology · doi:10.1016/j.eururo.2023.03.037 · Cited by 66 · see citing works

What Should Data Science Education Do With Large Language Models?

Tu, X., Zou, J., Su, W., & Zhang, L. (2024) · Harvard Data Science Review · doi:10.1162/99608f92.bff007ab · Cited by 66 · see citing works

Empowering Education with LLMs - The Next-Gen Interface and Content Generation

Moore, S., Tong, R. M., Singh, A., Liu, Z., Hu, X., Lu, Y., Liang, J., Cao, C., Khosravi, H., Denny, P. C., et al. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-36336-8_4 · Cited by 64 · see citing works

Harnessing large language models (LLMs) for candidate gene prioritization and selection

Toufiq, M., Rinchai, D., Bettacchioli, É., Kabeer, B. S. A., Khan, T., Subba, B., White, O., Yurieva, M., George, J., Jourde‐Chiche, N., et al. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04576-8 · Cited by 64 · see citing works

Large language models will not replace healthcare professionals: curbing popular fears and hype.

Thirunavukarasu, A. J. (2023) · Journal of the Royal Society of Medicine · doi:10.1177/01410768231173123 · Cited by 63 · see citing works

Assessing the Accuracy and Clinical Utility of ChatGPT in Laboratory Medicine

Muñoz‐Zuluaga, C., Zhao, Z., Wang, F., Greenblatt, M. B., & Yang, H. S. (2023) · Clinical Chemistry · doi:10.1093/clinchem/hvad058 · Cited by 61 · see citing works

Large Language Models Understand and Can be Enhanced by Emotional Stimuli

Li, C., Wang, J., Zhang, Y., Zhu, K., Hou, W., Lian, J., Luo, F., Yang, Q., & Xie, X. (2023) · arXiv · doi:10.48550/arxiv.2307.11760 · Cited by 59 · see citing works

ChatGPT-4: Transforming Medical Education and Addressing Clinical Exposure Challenges in the Post-pandemic Era

Lower, K., Seth, I., Lim, B., & Seth, N. (2023) · Indian Journal of Orthopaedics · doi:10.1007/s43465-023-00967-7 · Cited by 50 · see citing works

Assessing the Strengths and Weaknesses of Large Language Models

Lappin, S. (2023) · Journal of Logic Language and Information · doi:10.1007/s10849-023-09409-x · Cited by 47 · see citing works

HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)

Ali, T., & Kostakos, P. (2023) · arXiv · doi:10.48550/arxiv.2309.16021 · Cited by 47

How to approach machine learning-based prediction of drug/compound–target interactions

Ataş, H., & Doğan, T. (2023) · Journal of Cheminformatics · doi:10.1186/s13321-023-00689-w · Cited by 46 · see citing works

WHO declares the end of the COVID-19 global health emergency: lessons and recommendations from the perspective of ChatGPT/GPT-4

Cheng, K., Wu, C., Gu, S., Lu, Y., Wu, H., & Li, C. (2023) · International Journal of Surgery · doi:10.1097/js9.0000000000000521 · Cited by 46 · see citing works

Large Language Models (LLMs) and Empathy – A Systematic ReviewPreprint

Sorin, V., Brin, D., Barash, Y., Konen, E., Charney, A. W., Nadkarni, G. N., & Klang, E. (2023) · medRxiv · doi:10.1101/2023.08.07.23293769 · Cited by 45 · see citing works

Evaluating GPT-4-based ChatGPT's clinical potential on the NEJM quiz

Ueda, D., Walston, S. L., Matsumoto, T., Deguchi, R., Tatekawa, H., & Miki, Y. (2024) · BMC Digital Health · doi:10.1186/s44247-023-00058-5 · Cited by 45 · see citing works

A descriptive study based on the comparison of ChatGPT and evidence-based neurosurgeons

Liu, J., Zheng, J., Cai, X., Wu, D., & Yin, C. (2023) · iScience · doi:10.1016/j.isci.2023.107590 · Cited by 44 · see citing works

Evaluation of GPT-4 for 10-year cardiovascular risk prediction: Insights from the UK Biobank and KoGES data

Han, C., Kim, D. W., Kim, S., You, S. C., Park, J. Y., Bae, S., & Yoon, D. (2024) · iScience · doi:10.1016/j.isci.2024.109022 · Cited by 41 · see citing works

Leveraging Large Language Models for Multiple Choice Question AnsweringPreprint

Robinson, J. A., Rytting, C. M., & Wingate, D. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2210.12353 · Cited by 40 · see citing works

Caution with AI-generated content in biomedicine

Zhavoronkov, A. (2023) · Nature Medicine · doi:10.1038/d41591-023-00014-w · Cited by 39 · see citing works

Social media: A new tool for outbreak surveillance

Wilson, A. E., Lehmann, C. U., Saleh, S. N., Hanna, J. J., & Medford, R. J. (2021) · Antimicrobial Stewardship & Healthcare Epidemiology · doi:10.1017/ash.2021.225 · Cited by 39 · see citing works

ChatGPT: when the artificial intelligence meets standardized patients in clinical training

Liu, X., Wu, C., Lai, R., Lin, H., Xu, Y., Lin, Y., & Zhang, W. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04314-0 · Cited by 37 · see citing works

ChatGPT is not the solution to physicians’ documentation burden

Preiksaitis, C. M., Sinsky, C. A., & Rose, C. C. (2023) · Nature Medicine · doi:10.1038/s41591-023-02341-4 · Cited by 36 · see citing works

Telemedicine: a Bridge Over Knowledge Gaps in Healthcare

Eisenstein, E., Kopacek, C., Cavalcante, S. S., Neves, A. C., Fraga, G. P., & Messina, L. A. (2020) · Current Pediatrics Reports · doi:10.1007/s40124-020-00221-w · Cited by 35 · see citing works

Large language models (LLM) and ChatGPT: a medical student perspective

Perera Molligoda Arachchige, A. S. (2023) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-023-06227-y · Cited by 35 · see citing works

Interventions to optimize medication use in nursing homes: a narrative review

Spinewine, A., Evrard, P., & Hughes, C. M. (2021) · European Geriatric Medicine · doi:10.1007/s41999-021-00477-5 · Cited by 34 · see citing works

MYCRUNCHGPT: A LLM ASSISTED FRAMEWORK FOR SCIENTIFIC MACHINE LEARNING

Kumar, V., Gleyzer, L., Kahana, A., Shukla, K., & Karniadakis, G. E. (2023) · Journal of Machine Learning for Modeling and Computing · doi:10.1615/jmachlearnmodelcomput.2023049518 · Cited by 34 · see citing works

A case study demonstrating applications of ChatGPT in the clinical management of treatment-resistant schizophrenia.

Galido, P. V., Butala, S., Chakerian, M., & Agustines, D. (2023) · Cureus · doi:10.7759/cureus.38166 · Cited by 29 · see citing works

How could ChatGPT impact my practice as an intensivist? An overview of potential applications, risks and limitations

Komorowski, M., Lopez, M. D. P. A., & Chang, A. C. (2023) · Intensive Care Medicine · doi:10.1007/s00134-023-07096-7 · Cited by 29 · see citing works

ChatGPT and large language models in gastroenterology

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MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks

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Software Testing with Large Language Models: Survey, Landscape, and VisionPreprint

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Evaluating Recommendations About Atrial Fibrillation for Patients and Clinicians Obtained From Chat-Based Artificial Intelligence Algorithms

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How can we transform travel medicine by leveraging on AI-powered search engines?

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Building Emotional Support Chatbots in the Era of LLMsPreprint

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Plan, Generate and Match: Scientific Workflow Recommendation with Large Language Models

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Writing medical papers using large-scale language models: a perspective from the Japanese Journal of Radiology

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Evolving Methods to Assess Chatbot Performance in Health Sciences Research

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Chatbots, Artificial Intelligence, and the Future of Scientific Reporting

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AI-link omnipotent pathological robot: Bridging medical meta-universe to real-world diagnosis and therapy

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WHO declares end of mpox global health emergency: first glance from a perspective of ChatGPT/GPT-4

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Letter to the Editor in Response to article by Vaishya et al ChatGPT: Is this version good for healthcare and research

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LARGE LANGUAGE MODELS (LLMS) AND CHATGPT FOR BIOMEDICINE

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Large language models in patient education: a scoping review of applications in medicine

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Large Language Models in Healthcare and Medical Applications: A Review

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Large language models for disease diagnosis: a scoping review

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Revolutionizing Health Care: The Transformative Impact of Large Language Models in Medicine

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Large Language Models in Worldwide Medical Exams: Platform Development and Comprehensive Analysis

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Scientific evidence for clinical text summarization using large language models: scoping review

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Large Language Models in Medicine: Clinical Applications, Technical Challenges, and Ethical Considerations

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Integrating ChatGPT in Orthopedic Education for Medical Undergraduates: Randomized Controlled Trial

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Comparing Diagnostic Accuracy of Clinical Professionals and Large Language Models: Systematic Review and Meta-Analysis

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AI-Powered Problem- and Case-based Learning in Medical and Dental Education: A Systematic Review and Meta-analysis

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Large Language Models in Medical Diagnostics: Scoping Review With Bibliometric Analysis

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Evaluating the Impact of Artificial Intelligence (AI) on Clinical Documentation Efficiency and Accuracy Across Clinical Settings: A Scoping Review

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Custom Large Language Models Improve Accuracy: Comparing Retrieval Augmented Generation and Artificial Intelligence Agents to Noncustom Models for Evidence‐Based Medicine

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Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer

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Innovation and application of Large Language Models (LLMs) in dentistry – a scoping review

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Racial bias in AI-mediated psychiatric diagnosis and treatment: a qualitative comparison of four large language models

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Use of large language models as artificial intelligence tools in academic research and publishing among global clinical researchers

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A survey for large language models in biomedicine

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Large language models in medicine: A review of current clinical trials across healthcare applications

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Large language model for knowledge synthesis and AI-enhanced biomanufacturing

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Generative AI chatbots for reliable cancer information: Evaluating web-search, multilingual, and reference capabilities of emerging large language models

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Large Language Models and Their Applications in Drug Discovery and Development: A Primer

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Opportunities and Challenges for Large Language Models in Primary Health Care

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Concordance of ChatGPT artificial intelligence decision-making in colorectal cancer multidisciplinary meetings: retrospective study

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A multi-dimensional performance evaluation of large language models in dental implantology: comparison of ChatGPT, DeepSeek, Grok, Gemini and Qwen across diverse clinical scenarios

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Comparative analysis of large language models in clinical diagnosis: performance evaluation across common and complex medical cases

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Clinical insights: A comprehensive review of language models in medicine

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AI Chatbot Use and Disclosure for Mental Health Among US Adolescents and Young Adults

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Ethical and practical challenges of generative AI in healthcare and proposed solutions: a survey

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Advantages and limitations of large language models for antibiotic prescribing and antimicrobial stewardship

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Evaluating ChatGPT and Google Gemini Performance and Implications in Turkish Dental Education

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Evaluating ChatGPT’s diagnostic potential for pathology images

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Perspectives and Experiences With Large Language Models in Health Care: Survey Study

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Large Language Models for Adverse Drug Events: A Clinical Perspective

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Reproducible generative artificial intelligence evaluation for health care: a clinician-in-the-loop approach

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Factors influencing medical students’ adoption of AI educational agents: an extended UTAUT model

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Coal Mine Accident Risk Analysis with Large Language Models and Bayesian Networks

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Evolution of AI in anatomy education study based on comparison of current large language models against historical ChatGPT performance

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Comparison of Gemini Advanced and ChatGPT 4.0’s Performances on the Ophthalmology Resident Ophthalmic Knowledge Assessment Program (OKAP) Examination Review Question Banks

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A Review of Innovative Medical Rehabilitation Systems with Scalable AI-Assisted Platforms for Sensor-Based Recovery Monitoring

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Evaluation of deepseek, gemini, ChatGPT-4o, and perplexity in responding to salivary gland cancer

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Generative artificial intelligence (GAI) usage guidelines for scholarly publishing: a cross-sectional study of medical journals

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Large Language Models in Critical Care Medicine: Scoping Review

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A longitudinal analysis of declining medical safety messaging in generative AI models

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Digital Diagnostics: The Potential of Large Language Models in Recognizing Symptoms of Common Illnesses

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Fine-Tuning Methods for Large Language Models in Clinical Medicine by Supervised Fine-Tuning and Direct Preference Optimization: Comparative Evaluation

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Comparative Evaluation of Responses from ChatGPT-5, Gemini 2.5 Flash, Grok 4, and Claude Sonnet-4 Chatbots to Questions About Endodontic Iatrogenic Events

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Integrating LLMs and Knowledge Graphs for Medical AI: Advances, Challenges, and Future Directions

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Challenges and applications in generative AI for clinical tabular data in physiology

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Open-Weight Language Models and Retrieval-Augmented Generation for Automated Structured Data Extraction from Diagnostic Reports: Assessment of Approaches and Parameters

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Assessing the Role of Large Language Models Between ChatGPT and DeepSeek in Asthma Education for Bilingual Individuals: Comparative Study

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Unlocking the potential of advanced large language models in medication review and reconciliation: A proof-of-concept investigation

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Vision-language models for automated video analysis and documentation in laparoscopic surgery: a proof-of-concept study

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Generative artificial intelligence and large language models in smart healthcare applications: Current status and future perspectives

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Comparing AI and human decision-making mechanisms in daily collaborative experiments

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Large Language Models Evaluation of Medical Licensing Examination Using GPT-4.0, ERNIE Bot 4.0, and GPT-4o

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LLM-Based Generative AI in Medicine: Analysis of Current Research Trends With BERTopic

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Omission and hallucination prevalence of clinical guidelines in diagnostic large language model outputs

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Hepatic encephalopathy post-TIPS: Current status and prospects in predictive assessment

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The Development Landscape of Large Language Models for Biomedical Applications

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Diagnostic performance of Large Language Models (LLMs) compared with physicians in sleep medicine

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Advancing healthcare with large language models: A scoping review of applications and future directions

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StressLLM: Large Language Models for Stress Prediction via Wearable Sensor Data

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Performance analysis of large language models Chatgpt-4o, OpenAI O1, and OpenAI O3 mini in clinical treatment of pneumonia: a comparative study

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AI in Medical Questionnaires: Scoping Review

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Large Language Models and the Analyses of Adherence to Reporting Guidelines in Systematic Reviews and Overviews of Reviews (PRISMA 2020 and PRIOR)

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Large language model application in emergency medicine and critical care

Hwai, H., Ho, Y.-J., Wang, C., & Huang, C. (2024) · Journal of the Formosan Medical Association · doi:10.1016/j.jfma.2024.08.032 · Cited by 13 · see citing works

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Kang, L., Hu, J. M., Cai, K., Jing, W., Liu, M., & Liang, W. (2024) · Global Transitions · doi:10.1016/j.glt.2024.10.004 · Cited by 13 · see citing works

Reliability and efficiency of ChatGPT 3.5 and 4.0 as a tool for scalenovertebral triangle anatomy education

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Leon, M., Ruaengsri, C., Pelletier, G., Bethencourt, D., Shibata, M., Flores, M. Q., & Shudo, Y. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13216543 · Cited by 12 · see citing works

Evaluating Artificial Intelligence-Generated Patient Education Materials for Bariatric Surgery: Comparative Analysis of Response Quality, Reliability, and Readability Across ChatGPT and DeepSeek Models

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Performance of ChatGPT and Large Language Models on Medical Licensing Exams Worldwide: A Systematic Review and Network Meta-Analysis With Meta-Regression

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Generative AI in medicine: A thorough examination of applications, challenges, and future perspectives

Jayasrilakshmi, S., & Mahapatra, A. (2026) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2026.111469 · Cited by 12 · see citing works

Large language models for clinical artificial intelligence in healthcare a systematic review

Ghnemat, R., & Saleh, A. (2026) · Discover Artificial Intelligence · doi:10.1007/s44163-025-00784-x · Cited by 12 · see citing works

MedBot vs RealDoc: efficacy of large language modeling in physician-patient communication for rare diseases

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CMedRAGBot: A Chinese Medical Chatbot Based on Graph RAG and Large Language Models

Zhang, D., Du, H., Wang, X., Zhu, M., Pang, X., Wei, D., & Wang, X. (2025) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-025-00715-5 · Cited by 12 · see citing works

Automated analyses of risk of bias and critical appraisal of systematic reviews (ROBIS and AMSTAR 2): a comparison of the performance of 4 large language models

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Novel AI applications in systematic review: gPT-4 assisted data extraction, analysis, review of bias

Kim, J. K., Chua, M. E., Li, T. G., Rickard, M., & Lorenzo, A. J. (2025) · BMJ Evidence-Based Medicine · doi:10.1136/bmjebm-2024-113066 · Cited by 11 · see citing works

Evaluating the Performance of ChatGPT 3.5 and 4.0 on StatPearls Oculoplastic Surgery Text- and Image-Based Exam Questions

Gill, G. S., Blair, J., & Litinsky, S. M. (2024) · Cureus · doi:10.7759/cureus.73812 · Cited by 11 · see citing works

Evaluation of the ability of large language models to self-diagnose oral diseases

Zhuang, S., Zeng, Y., Lin, S., Chen, X., Xin, Y., Li, H., Lin, Y., Zhang, C., & Lin, Y. (2024) · iScience · doi:10.1016/j.isci.2024.111495 · Cited by 11 · see citing works

Healthcare providers’ perceptions of artificial intelligence in diabetes care: A cross-sectional study in China

Mo, Y., Zhao, F., Yuan, L., Xing, Q., Zhou, Y., Wu, Q., Li, C., Lin, J., Wu, H., Deng, S., et al. (2025) · International Journal of Nursing Sciences · doi:10.1016/j.ijnss.2025.04.013 · Cited by 11 · see citing works

VISION: a modular AI assistant for natural human-instrument interaction at scientific user facilities

Mathur, S., van der Vleuten, N., Yager, K. G., & Tsai, E. H. R. (2025) · Machine Learning Science and Technology · doi:10.1088/2632-2153/add9e4 · Cited by 11 · see citing works

AI Veterinary Assistance: Enhancing Clinical Decision-Making in Animal Healthcare

Jin, Y.-G., Wu, G., Seo, J. Y., Park, S.-J., Hur, S.-H., Aliyeva, D., Park, J.-H., & Kim, K.-M. (2025) · IEEE Access · doi:10.1109/access.2025.3587787 · Cited by 11 · see citing works

A prompt framework for enhancing LLM-based explainability of medical machine learning models: an intensive care unit application

Lee, S., Cho, W. I., Lee, Y., Kim, D. J., Nam, K. H., Lee, S. M., Suh, J., & Ko, T. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-03239-6 · Cited by 11 · see citing works

Evaluating Vision-Language Models for hematology image Classification: Performance Analysis of CLIP and its Biomedical AI Variants

Patel, T., El-Sayed, H., & Sarker, M. K. (2024) · Conference of Open Innovations Association (FRUCT) · doi:10.23919/fruct64283.2024.10749850 · Cited by 10 · see citing works

Evaluating the Feasibility of ChatGPT-4 as a Knowledge Resource in Bariatric Surgery: A Preliminary Assessment

Leng, Y., Yang, Y., Liu, J., Jiang, J., & Zhou, C. (2025) · Obesity Surgery · doi:10.1007/s11695-024-07666-8 · Cited by 10 · see citing works

Awareness and use of generative AI-powered tools: results of one-year follow-up prospective cross-sectional global survey

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Application of Generative Artificial Intelligence for Physician and Patient Oncology Letters—AI-OncLetters

Shahnam, A., Nindra, U., Hitchen, N., Tang, J., Hong, M., Hong, J. H., Au‐Yeung, G., Chua, W. M., Ng, W. L., Hopkins, A. M., et al. (2025) · JCO Clinical Cancer Informatics · doi:10.1200/cci-24-00323 · Cited by 10 · see citing works

Large Language Models Using Clinical Text in Pediatrics

Huang, T., Tse, G., Pageler, N. M., & Bannett, Y. (2026) · JAMA Network Open · doi:10.1001/jamanetworkopen.2026.2443 · Cited by 10 · see citing works

Artificial Intelligence in Speech-Language Pathology and Dysphagia: A Review From Latin American Perspective and Pilot Test of LLMs for Rehabilitation Planning

Gallano, G., Giglio, A., & Ferre, A. (2025) · Journal of Voice · doi:10.1016/j.jvoice.2025.04.010 · Cited by 9 · see citing works

ChatGPT’s Attitude, Knowledge, and Clinical Application in Geriatrics Practice and Education: Exploratory Observational Study

Cheng, H. Y. (2024) · JMIR Formative Research · doi:10.2196/63494 · Cited by 9 · see citing works

Realising the potential impact of artificial intelligence for rare diseases – A framework

Groza, T., Chan, C., Pearce, D. A., & Baynam, G. S. (2024) · Rare · doi:10.1016/j.rare.2024.100057 · Cited by 9 · see citing works

Integrating Large language models into radiology workflow: Impact of generating personalized report templates from summary

Gupta, A. K., Hussain, M., Nikhileswar, K., Rastogi, A., & Rangarajan, K. (2025) · European Journal of Radiology · doi:10.1016/j.ejrad.2025.112198 · Cited by 9 · see citing works

Enhancing large language models by integrating domain knowledge based data-driven small models for anomaly diagnosis and trouble shooting in wastewater treatment plants

Xu, S., Wang, X., & Bi, X. (2025) · Journal of environmental chemical engineering · doi:10.1016/j.jece.2025.117379 · Cited by 9 · see citing works

Precision and Personalization: How Large Language Models Redefining Diagnostic Accuracy in Personalized Medicine — A Systematic Literature Review

Aththanagoda, A. K. N. L., Kulathilake, K. A. S. H., & Abdullah, N. A. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3584179 · Cited by 9 · see citing works

A comparative evaluation of publicly available large language models in the assessment of CTG traces according to the FIGO criteria

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GenAI in nutritional sciences (GAINS): A systematic review and reporting framework for future research

Hieronimus, B., Lopez-Aguirre, M.-L., Birringer, M., & Podszun, M. C. (2025) · Nutrition Research · doi:10.1016/j.nutres.2025.09.011 · Cited by 9 · see citing works

The impact of large language models on medical research and patient care: A systematic review of current trends, challenges, and future innovations

Asif, S., Hadi, F., Ain, Q. U., Yan, Y., Wang, V. Y., & Xu, D. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100847 · Cited by 5 · see citing works

Large language models in medicine: A systematic review of applications in medical, healthcare, and educational contexts

Navarro, H. J., Rodriguez, C. L. S., & Galpin, I. (2025) · Periodicals of Engineering and Natural Sciences (PEN) · doi:10.21533/pen.v13.i3.460 · Cited by 6 · see citing works

The Transformative Role of Large Language Models in Medicine

Banu, G. S., Joița, D., & Priescu, I. (2024) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-62502-2_73 · Cited by 1 · see citing works

Large Language Models in Medicine: Applications, Challenges, and Future Directions

Yu, E., Chu, X., Zhang, W., Meng, X., Yang, Y., Ji, X., & Wu, C. (2025) · International Journal of Medical Sciences · doi:10.7150/ijms.111780 · Cited by 144 · see citing works

Large Language Models in Medicine: Application Status and Challenges

Chen, Z., Lu, Y., Zeng, Y., Tian, D., Li, Y., & Li, F. (2025) · AI medicine. · doi:10.53941/aim.2025.100008