LLMs in medicine: The need for advanced evaluation systems for disruptive technologies
-
-
REFERENCES
[1] Singhal, K., Azizi, S., Tu, T., et al. (2023). Large language models encode clinical knowledge. Nature 620: 172-180. https://doi.org/10.1038/s41586-023-06291-2. [2] Thirunavukarasu, A.J., Ting, D.S.J., Elangovan, K., et al. (2023). Large language models in medicine. Nat. Med. 29(8): 1930-1940. https://doi.org/10.1038/s41591-023-02448-8. [3] Xu, Y., Liu, X., Cao, X., et al. (2021). Artificial intelligence: A powerful paradigm for scientific research. Innovation 2(4): 100179. [4] Shah, N.H., Entwistle, D., and Pfeffer, M.A. (2023). Creation and Adoption of Large Language Models in Medicine. JAMA 330(9): 866-869. https://doi.org/10.1001/jama.2023.14217. [5] Peng, C., Yang, X., Chen, A., et al. (2023). A study of generative large language model for medical research and healthcare. NPJ Digit. Med. 6(6): 210. https://doi.org/10.1038/s41746-023-00958-w. -
ABOUT THIS ARTICLE
Cite this article:
Tang Y.-D., Dong E.-D., and Gao W. (2024). LLMs in medicine: The need for advanced evaluation systems for disruptive technologies. The Innovation 5(3), 100622. https://doi.org/10.1016/j.xinn.2024.100622
Welcome!
To request copyright permission to republish or share portions of our works, please visit Copyright Clearance Center's (CCC) Marketplace website at marketplace.copyright.com.
Export File
Citation
Tang Y.-D., Dong E.-D., and Gao W. (2024). LLMs in medicine: The need for advanced evaluation systems for disruptive technologies. The Innovation 5(3), 100622. https://doi.org/10.1016/j.xinn.2024.100622
Format
Content
DownLoad:
-
Figure 1.
Interdisciplinary impact network of LLMs in health care
