Automatically determining cause of death from verbal autopsy narratives.

ABSTRACT:

Background

A verbal autopsy (VA) is a post-hoc written interview report of the symptoms preceding a person's death in cases where no official cause of death (CoD) was determined by a physician. Current leading automated VA coding methods primarily use structured data from VAs to assign a CoD category. We present a method to automatically determine CoD categories from VA free-text narratives alone.

Methods

After preprocessing and spelling correction, our method extracts word frequency counts from the narratives and uses them as input to four different machine learning classifiers: naïve Bayes, random forest, support vector machines, and a neural network.

Results

For individual CoD classification, our best classifier achieves a sensitivity of.770 for adult deaths for 15

SUBMITTER: Jeblee S 

PROVIDER: S-EPMC6617656 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature