Mortality-Risk Prediction Model from Road-Traffic Injury in Drunk Drivers: Machine Learning Approach.

Journal: International journal of environmental research and public health

Published Date: Oct 8, 2021

Abstract

BACKGROUND: Alcohol-related road-traffic injury is the leading cause of premature death in middle- and lower-income countries, including Thailand. Applying machine-learning algorithms can improve the effectiveness of driver-impairment screening strategies by legal limits.

Authors

Wachiranun Sirikul

Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.
Nida Buawangpong

Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.
Ratana Sapbamrer

Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.
Penprapa Siviroj

Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand.

Keywords

Accidents, Traffic Algorithms Cross-Sectional Studies Logistic Models Machine Learning Neural Networks, Computer

External Resources

View on PubMed Access via DOI PubMed (34639839)

Mortality-Risk Prediction Model from Road-Traffic Injury in Drunk Drivers: Machine Learning Approach.

Abstract

Authors

Keywords

External Resources

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