Can natural language processing models extract and classify instances of interpersonal violence in mental healthcare electronic records: an applied evaluative study.

ABSTRACT:

Objective

This paper evaluates the application of a natural language processing (NLP) model for extracting clinical text referring to interpersonal violence using electronic health records (EHRs) from a large mental healthcare provider.

Design

A multidisciplinary team iteratively developed guidelines for annotating clinical text referring to violence. Keywords were used to generate a dataset which was annotated (ie, classified as affirmed, negated or irrelevant) for: presence of violence, patient status (ie, as perpetrator, witness and/or victim of violence) and violence type (domestic, physical and/or sexual). An NLP approach using a pretrained transformer model, BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining) was fine-tuned on t

SUBMITTER: Botelle R 

PROVIDER: S-EPMC8852656 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature