Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.

ABSTRACT:

Objective

Alcohol misuse is present in over a quarter of trauma patients. Information in the clinical notes of the electronic health record of trauma patients may be used for phenotyping tasks with natural language processing (NLP) and supervised machine learning. The objective of this study is to train and validate an NLP classifier for identifying patients with alcohol misuse.

Materials and methods

An observational cohort of 1422 adult patients admitted to a trauma center between April 2013 and November 2016. Linguistic processing of clinical notes was performed using the clinical Text Analysis and Knowledge Extraction System. The primary analysis was the binary classification of alcohol misuse. The Alcohol Use Disorders Identification Test served as the reference standard

SUBMITTER: Afshar M 

PROVIDER: S-EPMC6657384 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature