Comparison of rule- and large language model-based phenotype extraction from clinical notes for neurofibromatosis type 1.

ABSTRACT:

Introduction

Neurofibromatosis type 1 (NF1) is a rare genetic disorder affecting multiple organ systems with significant clinical heterogeneity. Managing individuals with NF1 is challenging due to variability in disease progression and outcomes and limited early risk assessment tools.

Objective

This study aims to develop an effective, generalizable, user-friendly clinical entity extraction pipeline for identifying NF1-related phenotypes from unstructured clinical notes to enhance research and risk-modeling efforts. We compare the benefits of rule-based natural language processing (NLP) vs large language models (LLMs) for this purpose.

Materials and methods

Four phenotype extraction pipelines (3 LLM-based vs 1 rule-based) were developed to automatically extract selecte

SUBMITTER: Kaster L 

PROVIDER: S-EPMC12626218 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature