Large language models for oncological applications

Vera Sorin; Yiftach Barash; Eli Konen; Eyal Klang

doi:10.1007/s00432-023-04824-w

Large language models for oncological applications

J Cancer Res Clin Oncol. 2023 Sep;149(11):9505-9508. doi: 10.1007/s00432-023-04824-w. Epub 2023 May 9.

Authors

Vera Sorin^{1

2

3}, Yiftach Barash^{4

5

6}, Eli Konen^{4

6}, Eyal Klang^{4

5

7

6}

Affiliations

¹ Department of Diagnostic Imaging, Chaim Sheba Medical Center, Ramat Gan, Israel. [email protected].
² DeepVision Lab, Chaim Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel. [email protected].
³ Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel. [email protected].
⁴ Department of Diagnostic Imaging, Chaim Sheba Medical Center, Ramat Gan, Israel.
⁵ DeepVision Lab, Chaim Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel.
⁶ Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
⁷ Sami Sagol AI Hub, ARC, Chaim Sheba Medical Center, Ramat Gan, Israel.

PMID: 37160626
DOI: 10.1007/s00432-023-04824-w

Abstract

Large language models such as ChatGPT have gained public and scientific attention. These models may support oncologists in their work. Oncologists should be familiar with large language models to harness their potential while being aware of potential dangers and limitations.

Publication types

Letter

MeSH terms

Humans
Language*
Medical Oncology
Oncologists*