This paper is in the following e-collection/theme issue:

Public Health Informatics (93) Clinical Information and Decision Making (1407) Cardiovascular Disease Prevention (137) Artificial Intelligence (1371) Machine Learning (1465) Computer-Aided Diagnosis (128) Decision Support for Health Professionals (1185)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47095, first published .
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

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

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

Authors of this article:

Yuhan Deng1, 2 Author Orcid Image ;   Yuan Ma3 Author Orcid Image ;   Jingzhu Fu4, 5, 6 Author Orcid Image ;   Xiaona Wang7 Author Orcid Image ;   Canqing Yu4, 5, 6, 8 Author Orcid Image ;   Jun Lv4, 5, 6, 8 Author Orcid Image ;   Sailimai Man2, 4, 5, 6 Author Orcid Image ;   Bo Wang2, 5, 8 Author Orcid Image ;   Liming Li4, 5, 6, 8 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

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  1. El Emam K, Leung T, Malin B, Klement W, Eysenbach G. Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS). Journal of Medical Internet Research 2024;26:e52508 View
  2. Halushko O, Hurtovyi Y. Development and validation of a mathematical model for predicting the development of gastro-oesophageal reflux disease based on oesophagogastroduodenoscopy. Bulletin Of Medical And Biological Research 2024;6(1):15 View
  3. Zhang Y, Xue H, Xia H, Jiang X. Prediction models for cognitive frailty in community-dwelling older adults: A scoping review. Geriatric Nursing 2024;60:448 View