Extracting Family History Information From Electronic Health Records: Natural Language Processing Analysis.

ABSTRACT:

Background

The prognosis, diagnosis, and treatment of many genetic disorders and familial diseases significantly improve if the family history (FH) of a patient is known. Such information is often written in the free text of clinical notes.

Objective

The aim of this study is to develop automated methods that enable access to FH data through natural language processing.

Methods

We performed information extraction by using transformers to extract disease mentions from notes. We also experimented with rule-based methods for extracting family member (FM) information from text and coreference resolution techniques. We evaluated different transfer learning strategies to improve the annotation of diseases. We provided a thorough error analysis of the contributing factors tha

SUBMITTER: Rybinski M 

PROVIDER: S-EPMC8092929 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature