Information extraction from free text for aiding transdiagnostic psychiatry: constructing NLP pipelines tailored to clinicians' needs.

ABSTRACT:

Background

Developing predictive models for precision psychiatry is challenging because of unavailability of the necessary data: extracting useful information from existing electronic health record (EHR) data is not straightforward, and available clinical trial datasets are often not representative for heterogeneous patient groups. The aim of this study was constructing a natural language processing (NLP) pipeline that extracts variables for building predictive models from EHRs. We specifically tailor the pipeline for extracting information on outcomes of psychiatry treatment trajectories, applicable throughout the entire spectrum of mental health disorders ("transdiagnostic").

Methods

A qualitative study into beliefs of clinical staff on measuring treatment outcomes was con

SUBMITTER: Turner RJ 

PROVIDER: S-EPMC9206307 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature