A software pipeline for medical information extraction with large language models, open source and suitable for oncology.

ABSTRACT: In medical oncology, text data, such as clinical letters or procedure reports, is stored in an unstructured way, making quantitative analysis difficult. Manual review or structured information retrieval is time-consuming and costly, whereas Large Language Models (LLMs) offer new possibilities in natural language processing for structured Information Extraction (IE) from medical free text. This protocol describes a workflow (LLM-AIx) for extracting predefined clinical entities from unstructured oncology text using privacy-preserving LLMs. It addresses a key barrier in clinical research and care by enabling efficient information extraction to support decision-making and large-scale data analysis. It runs on local hospital infrastructure, eliminating the need to transfer patient data external

SUBMITTER: Wiest IC 

PROVIDER: S-EPMC12443949 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature