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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 Li
Published 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.
Keyphrases
  • public health
  • machine learning
  • risk assessment
  • coronary artery disease
  • healthcare
  • human health
  • mental health
  • fatty acid
  • artificial intelligence
  • heavy metals
  • global health
  • health information
  • social media