Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study.
Yuhan DengYuan MaJingzhu FuXiaona WangCanqing YuJun LvSailimai ManBo WangLiming LiPublished in: JMIR public health and surveillance (2023)
The combination of ML and logistic regression yielded a practical carotid plaque prediction model, and was of great public health implications in the early identification and risk assessment of carotid plaque among individuals with fatty liver.