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Formative Evaluation of Digital Health Interventions (3256) Artificial Intelligence (2146) Machine Learning (2085) Clinical Informatics (1329)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53654, first published .
Development of Cost-Effective Fatty Liver Disease Prediction Models in a Chinese Population: Statistical and Machine Learning Approaches

Development of Cost-Effective Fatty Liver Disease Prediction Models in a Chinese Population: Statistical and Machine Learning Approaches

Development of Cost-Effective Fatty Liver Disease Prediction Models in a Chinese Population: Statistical and Machine Learning Approaches

Authors of this article:

Liang Zhang1 Author Orcid Image ;   Yueqing Huang1 Author Orcid Image ;   Min Huang1 Author Orcid Image ;   Chun-Hua Zhao1 Author Orcid Image ;   Yan-Jun Zhang2 Author Orcid Image ;   Yi Wang3 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Yang B, Lu H, Ran Y. Advancing non-alcoholic fatty liver disease prediction: a comprehensive machine learning approach integrating SHAP interpretability and multi-cohort validation. Frontiers in Endocrinology 2024;15 View
  2. Chen S, Xu D, Hu D, Hu P, Huang T. Predicting Metabolic Dysfunction-Associated Fatty Liver Disease Phenotypes among Adults: A Two-Stage Contrastive Learning Method (Preprint). JMIR Medical Informatics 2025 View
  3. Pugliesi R, Ben Mansour K, Apitzsch J, Papachristodoulou A, Rafailidis V, Katz D. Meta-Analysis of AI Integration in Abdominal Imaging for Liver Fibrosis and MASLD: Evaluating Diagnostic Accuracy and Clinical Impact. Journal of Clinical Medicine 2025;14(23):8466 View
  4. Sun J, Sun X, Lu B, Deng B. Artificial intelligence in hepatopathy diagnosis and treatment: Big data analytics, deep learning, and clinical prediction models. World Journal of Gastroenterology 2025;31(46) View

Conference Proceedings

  1. Maurya S, Khatoon A, Hassan A, Badhan A, Rakhra M, Sarkar T. 2025 International Conference on Networks and Cryptology (NETCRYPT). Advanced Diagnostic Framework for Liver Disease Identification Utilizing Integrated Ensemble Machine Learning Models View
  2. Sarkar T, Rakhra M. 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). Advanced Diagnostic Framework for Liver Disease Identification Utilizing Integrated Ensemble Machine Learning Models View