التفاصيل البيبلوغرافية
| العنوان: |
Large language model use in clinical oncology. |
| المؤلفون: |
Carl, Nicolas, Schramm, Franziska, Haggenmüller, Sarah, Kather, Jakob Nikolas, Hetz, Martin J., Wies, Christoph, Michel, Maurice Stephan, Wessels, Frederik, Brinker, Titus J. |
| المصدر: |
NPJ Precision Oncology; 10/23/2024, Vol. 8 Issue 1, p1-17, 17p |
| مصطلحات موضوعية: |
LANGUAGE models, EVALUATION methodology, ONCOLOGY, HETEROGENEITY |
| مستخلص: |
Large language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, and the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, and compare methodological approaches and outcomes. This review includes 34 studies. LLMs are primarily evaluated on their ability to answer oncologic questions across various domains. The meta-analysis highlights a significant performance variance, influenced by diverse methodologies and evaluation criteria. Furthermore, differences in inherent model capabilities, prompting strategies, and oncological subdomains contribute to heterogeneity. The lack of use of standardized and LLM-specific reporting protocols leads to methodological disparities, which must be addressed to ensure comparability in LLM research and ultimately leverage the reliable integration of LLM technologies into clinical practice. [ABSTRACT FROM AUTHOR] |
|
Copyright of NPJ Precision Oncology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
Full Text Finder