Application of deep neural survival networks to the development of risk prediction models for diabetes mellitus, hypertension, and dyslipidemia.

ABSTRACT:

Objectives

: Although numerous risk prediction models have been proposed, few such models have been developed using neural network-based survival analysis. We developed risk prediction models for three cardiovascular disease risk factors (diabetes mellitus, hypertension, and dyslipidemia) among a working-age population in Japan using DeepSurv, a deep feed-forward neural network.

Methods

: Data were obtained from the Japan Epidemiology Collaboration on Occupational Health Study. A total of 51 258, 44 197, and 31 452 individuals were included in the development of risk models for diabetes mellitus, hypertension, and dyslipidemia, respectively; two-thirds of whom were used to develop prediction models, and the rest were used to validate the models. We compared the performances

SUBMITTER: Sasagawa Y 

PROVIDER: S-EPMC10842670 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature