Back to search

Article

Multidisciplinary large language model agent teams for precision oncology enhance complex gynecologic oncology decision support

2025-11-02

Abstract excerpt

Large language models can help with clinical decision-making tasks. Complex oncology cases are best managed through multidisciplinary tumor boards but are difficult to do so due to their expense. The MDAT framework is proposed to mimic tumor board-style collaboration. Some LLMs are prompted to act like experts. They first analyze the prompt from their respective perspectives. Then the decision-making takes place t...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
41f6e52b-52ac-503d-8b88-3091e8a6567b
DOI
10.1101/2025.10.30.25339199
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Multidisciplinary large language model agent teams for precision oncology enhance complex gynecologic oncology decision supportDOI 10.1101/2025.10.30.25339199
Select a neighboring publication to make it the new centre.