Development and Validation of Machine Models Using Natural Language Processing to Classify Substances Involved in Overdose Deaths.

ABSTRACT:

Importance

Overdose is one of the leading causes of death in the US; however, surveillance data lag considerably from medical examiner determination of the death to reporting in national surveillance reports.

Objective

To automate the classification of deaths related to substances in medical examiner data using natural language processing (NLP) and machine learning (ML).

Design, setting, and participants

Diagnostic study comparing different natural language processing and machine learning algorithms to identify substances related to overdose in 10 health jurisdictions in the US from January 1, 2020, to December 31, 2020. Unstructured text from 35 433 medical examiner and coroners' death records was examined.

Exposures

Text from each case was manually classified

SUBMITTER: Goodman-Meza D 

PROVIDER: S-EPMC9361079 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature