Large language models will not replace healthcare professionals: curbing popular fears and hype.
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The unimodal focus on text-based operation does not fully capture the complex and diverse nature of health care practice.
“While this unimodal focus on text-based operation has been transformative in the medical field, it does not fully capture the complex and diverse nature of health care practice [8].”
From Multimodal Large Language Models in Health Care: Applications, Challenges, and Future Outlook. (2024) · cites this paper as [8]
The main text says clinical practice requires more than responding accurately to queries and includes practical tasks that LLMs are not equipped to replace. That supports the claim that text-based operation does not capture the full scope of healthcare. But the paper does not describe LLMs as uniformly unimodal: it says GPT-4 accepts images as well as text. It also discusses potential benefits in medicine rather than establishing that text-based operation has already been transformative there. (LLM, conf=0.86)
Experimental — accuracy not yet measuredMost current large language models (LLMs) are primarily limited to processing and generating textual content.
“However, most current LLMs are primarily limited to processing and generating textual content.”
From Multimodal Large Language Models in Health Care: Applications, Challenges, and Future Outlook. (2024) · cites this paper as [8]
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Cites
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Research works printed but not linked: 1
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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
Self-citationThe 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 · see citing works
Multimodal Large Language Models in Health Care: Applications, Challenges, and Future Outlook.
AlSaad, R., Abd-alrazaq, A., Boughorbel, S., Ahmed, A., Renault, M.-A., Damseh, R., & Sheikh, J. (2024) · Journal of medical Internet research · doi:10.2196/59505 · Cited by 349 · see citing works
“While this unimodal focus on text-based operation has been transformative in the medical field, it does not fully capture the complex and diverse nature of health care practice [8].”
Large Language Models for Chatbot Health Advice Studies: A Systematic Review
Huo, B., Boyle, A., Marfo, N., Tangamornsuksan, W., Steen, J. P., McKechnie, T., Lee, Y., Mayol, J., Antoniou, S. A., Thirunavukarasu, A. J., et al. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.57879 · Cited by 283 · see citing works
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Large Language Model Uncertainty Measurement and Calibration for Medical Diagnosis and Treatment
Savage, T., Wang, J., Gallo, R., Boukil, A., Patel, V., Ahmad Safavi-Naini, S. A., Soroush, A., & Chen, J. H. (2024) · doi:10.1101/2024.06.06.24308399 · Cited by 11 · see citing works
- Authors
- Thirunavukarasu, A. J.
- Affiliations
- University of Cambridge (GB)
- Corresponding author
- Thirunavukarasu, Arun James
- Venue
- Journal of the Royal Society of Medicine
- Publisher
- SAGE Publications
- Published
- 2023-05
- Volume
- 116
- Issue
- 5
- Pages
- 181-182
- ISSN
- 0141-0768 (ISSN-L)
- 1758-1095
- PMC
- PMC10331084
- OpenAlex
- W4377011132
- Cited by
- 63
- References
- 9
- Citations by year
- 2026: 11 · 2025: 19 · 2024: 17 · 2023: 16
- FWCI
- 2.34
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of the Royal Society of Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Keywords
- large language models, artificial intelligence in healthcare, healthcare workers, artificial intelligence adoption
- MeSH terms
- Delivery of Health Care, Fear, Health Personnel, Humans, Language
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