Natural Language Processing in a Clinical Decision Support System for the Identification of Venous Thromboembolism: Algorithm Development and Validation.

ABSTRACT:

Background

It remains unknown whether capturing data from electronic health records (EHRs) using natural language processing (NLP) can improve venous thromboembolism (VTE) detection in different clinical settings.

Objective

The aim of this study was to validate the NLP algorithm in a clinical decision support system for VTE risk assessment and integrated care (DeVTEcare) to identify VTEs from EHRs.

Methods

All inpatients aged ≥18 years in the Sixth Medical Center of the Chinese People's Liberation Army General Hospital from January 1 to December 31, 2021, were included as the validation cohort. The sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR-, respectively), area under the receiver operating characteristic curve (AUC), and F1-scores a

SUBMITTER: Jin ZG 

PROVIDER: S-EPMC10167583 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature