Large language models in oncology: a review
Large language models (LLMs) have demonstrated emergent human-like capabilities in natural language processing, leading to enthusiasm about their integration in healthcare environments. In oncology, where synthesising complex, multimodal data is essential, LLMs offer a promising avenue for supportin...
Saved in:
| Main Authors: | Fei-Fei Liu, David Chen, Srinivas Raman, Rod Parsa, Karl Swanson, John-Jose Nunez, Andrew Critch, Danielle S Bitterman |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2025-05-01
|
| Series: | BMJ Oncology |
| Online Access: | https://bmjoncology.bmj.com/content/4/1/e000759.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Large Language Model Applications for Health Information Extraction in Oncology: Scoping Review
by: David Chen, et al.
Published: (2025-03-01) -
Large language model use in clinical oncology
by: Nicolas Carl, et al.
Published: (2024-10-01) -
The potential of large language models to advance precision oncology
by: Shufan Liang, et al.
Published: (2025-05-01) -
Trial Factors Associated With Completion of Clinical Trials Evaluating AI: Retrospective Case-Control Study
by: David Chen, et al.
Published: (2024-09-01) -
Development and evaluation of large-language models (LLMs) for oncology: A scoping review
by: Namya Mehan, et al.
Published: (2025-08-01)