Estimating Nonfatal Gunshot Injury Locations With Natural Language Processing and Machine Learning Models.

ABSTRACT:

Importance

Nonfatal gunshot injuries are the most common firearm injury, but where they frequently occur remains unclear owing to data limitations. Natural language processing can be applied to medical text narratives of gunshot injury records to classify injury location and inform prevention efforts.

Objective

To examine the performance of natural language processing (NLP) and machine learning models to predict nonfatal gunshot injury locations and generate new national estimates of the locations in which these injuries occur.

Design, setting, and participants

Cross-sectional study of data from the National Electronic Injury Surveillance System Firearm Injury Surveillance Study on nonfatal gunshot injuries that occurred in the US between January 1, 1993, and December

SUBMITTER: Parker ST 

PROVIDER: S-EPMC7557517 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature