Machine-learning model to predict the cause of death using a stacking ensemble method for observational data.

ABSTRACT:

Objective

Cause of death is used as an important outcome of clinical research; however, access to cause-of-death data is limited. This study aimed to develop and validate a machine-learning model that predicts the cause of death from the patient's last medical checkup.

Materials and methods

To classify the mortality status and each individual cause of death, we used a stacking ensemble method. The prediction outcomes were all-cause mortality, 8 leading causes of death in South Korea, and other causes. The clinical data of study populations were extracted from the national claims (n = 174 747) and electronic health records (n = 729 065) and were used for model development and external validation. Moreover, we imputed the cause of death from the data of 3 US claims databases (

SUBMITTER: Kim C 

PROVIDER: S-EPMC8200274 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature