Large language models should be used as scientific reasoning engines, not knowledge databases
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Combining precision medicine tools with an LLM enhances its capabilities in problem solving, aligning with the concept of using LLMs as 'reasoning engines'.
“Our results demonstrate that combining precision medicine tools with an LLM enhances its capabilities in problem solving, aligning with the concept of using LLMs as ‘reasoning engines’ (ref. 30).”
From Development and validation of an autonomous artificial intelligence agent for clinical decision-making in oncology (2025) · cites this paper as [30]
Cites
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
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y. T., Li, Y., Lundberg, S., et al. (2023) · arXiv · doi:10.48550/arxiv.2303.12712 · Cited by 1,526 · see citing works
GPT-4 is here: what scientists think
Sanderson, K. (2023) · Nature · doi:10.1038/d41586-023-00816-5 · Cited by 262 · see citing works
Will ChatGPT transform healthcare?
(2023) · Nature Medicine · doi:10.1038/s41591-023-02289-5 · Cited by 214 · 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
AI science search engines are exploding in number — are they any good?
Sanderson, K. (2023) · Nature · doi:10.1038/d41586-023-01273-w · Cited by 27 · see citing works
Not a generative AI–generated Editorial
(2023) · Nature Cancer · doi:10.1038/s43018-023-00531-0 · Cited by 4 · see citing works
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Ferber, D., El Nahhas, O. S. M., Wölflein, G., Wiest, I. C., Clusmann, J., Leßmann, M.-E., Foersch, S., Lammert, J., Tschochohei, M., Jäger, D., et al. (2025) · Nature Cancer · doi:10.1038/s43018-025-00991-6 · Cited by 175 · see citing works
Self-citationComparative Analysis of Multimodal Large Language Model Performance on Clinical Vignette Questions
Han, T., Adams, L. C., Bressem, K. K., Busch, F., Nebelung, S., & Truhn, D. (2024) · JAMA · doi:10.1001/jama.2023.27861 · Cited by 83 · see citing works
Self-citationMedical large language models are susceptible to targeted misinformation attacks
Han, T., Nebelung, S., Khader, F., Wang, T., Müller-Franzes, G., Kuhl, C., Försch, S., Kleesiek, J., Haarburger, C., Bressem, K. K., et al. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01282-7 · Cited by 62 · see citing works
Self-citationESMO guidance on the use of Large Language Models in Clinical Practice (ELCAP)
Wong, E. Y. T., Verlingue, L., Aldea, M., Franzoi, M. A., Umeton, R., Halabi, S., Harbeck, N., Indini, A., Prelaj, A., Romano, E., et al. (2025) · Annals of Oncology · doi:10.1016/j.annonc.2025.09.001 · Cited by 44 · see citing works
Self-citationMeddeb, A., Ebert, P., Bressem, K. K., Desser, D., Dell'Orco, A., Bohner, G., Kleine, J. F., Siebert, E., Grauhan, N., Brockmann, M. A., et al. (2025) · Journal of NeuroInterventional Surgery · doi:10.1136/jnis-2024-022078 · Cited by 27 · see citing works
Multimodal Large Language Models are Generalist Medical Image Interpreters
Han, T., Adams, L. C., Nebelung, S., Kather, J. N., Bressem, K. K., & Truhn, D. (2023) · doi:10.1101/2023.12.21.23300146 · Cited by 18 · see citing works
Self-citationCoevolution of large language models with physical models boosts advanced battery research
Li, J.-H., Hu, Y., Xia, G., Mo, W., Li, B., Jia, Y., Gao, Y., Xuan, F., Liu, H., & Lian, C. (2025) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2025.102553 · Cited by 2 · see citing works
- Authors
- Truhn, D., Reis-Filho, J. S., & Kather, J. N.
- Affiliations
- Universitätsklinikum Aachen (DE)
- Memorial Sloan Kettering Cancer Center (US)
- Else Kröner Fresenius Center for Digital Health (DE)
- Corresponding author
- Kather, Jakob Nikolas
- Venue
- Nature Medicine
- Published
- 2023-10-18
- Volume
- 29
- Issue
- 12
- Pages
- 2983-2984
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- OpenAlex
- W4387744047
- Cited by
- 102
- References
- 7
- Citations by year
- 2026: 29 · 2025: 36 · 2024: 34 · 2023: 3
- FWCI
- 4.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Keywords
- large language models, scientific reasoning, knowledge base, genetic testing
- MeSH terms
- Data Management, Language, Problem Solving
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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.
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