Proof-of-concept study of a small language model chatbot for breast cancer decision support - a transparent, source-controlled, explainable and data-secure approach.

ABSTRACT:

Purpose

Large language models (LLM) show potential for decision support in breast cancer care. Their use in clinical care is currently prohibited by lack of control over sources used for decision-making, explainability of the decision-making process and health data security issues. Recent development of Small Language Models (SLM) is discussed to address these challenges. This preclinical proof-of-concept study tailors an open-source SLM to the German breast cancer guideline (BC-SLM) to evaluate initial clinical accuracy and technical functionality in a preclinical simulation.

Methods

A multidisciplinary tumor board (MTB) is used as the gold-standard to assess the initial clinical accuracy in terms of concordance of the BC-SLM with MTB and comparing it to two publicly availa

SUBMITTER: Griewing S 

PROVIDER: S-EPMC11464535 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature