Use of SNOMED CT in Large Language Models: Scoping Review.

ABSTRACT:

Background

Large language models (LLMs) have substantially advanced natural language processing (NLP) capabilities but often struggle with knowledge-driven tasks in specialized domains such as biomedicine. Integrating biomedical knowledge sources such as SNOMED CT into LLMs may enhance their performance on biomedical tasks. However, the methodologies and effectiveness of incorporating SNOMED CT into LLMs have not been systematically reviewed.

Objective

This scoping review aims to examine how SNOMED CT is integrated into LLMs, focusing on (1) the types and components of LLMs being integrated with SNOMED CT, (2) which contents of SNOMED CT are being integrated, and (3) whether this integration improves LLM performance on NLP tasks.

Methods

Following the PRISMA-ScR (Pref

SUBMITTER: Chang E 

PROVIDER: S-EPMC11494256 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature