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

Reviews in Medical Informatics (116) Clinical Information and Decision Making (2004) Machine Learning (2167) Cardiac Risk and Cardiac Risk Calculators (111) Neurology and Neurosciences (295) Cancer Prognosis Models and Machine Learning (72) Data Science (373)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68898, first published .
The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review

The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review

The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review

Authors of this article:

Norah Hamad Alhumaidi1 Author Orcid Image ;   Doni Dermawan2 Author Orcid Image ;   Hanin Farhana Kamaruzaman3, 4 Author Orcid Image ;   Nasser Alotaiq5 Author Orcid Image
Article Authors Cited by (14) Tweetations (2) Metrics

Journals

  1. Wang H, Tian S, Bai S, Yang C, Jiang Z, Li N. Associations Between Thyroid Function and Periodontitis: A Machine Learning Approach Using NHANES. International Dental Journal 2025;75(5):100921 View
  2. Gomeni R, Bressolle‐Gomeni F. AI‐NLME: A New Artificial Intelligence‐Driven Nonlinear Mixed Effect Modeling Approach for Analyzing Longitudinal Data in Randomized Placebo‐Controlled Clinical Trials. Clinical and Translational Science 2025;18(9) View
  3. Ge L, Zhang Y, Peng G, Long M, Jin T, Lu B, Shao J, Li X. Serum alpha-1-microglobulin as a predictor of multiple complications in type 2 diabetes mellitus patients. World Journal of Diabetes 2025;16(10) View
  4. Oumaima M, Achraf B, Abdelilah J, Ahmed H. Non-invasive detection of Parkinson’s disease using voice analysis and machine learning techniques. International Journal of Speech Technology 2026;29(1) View
  5. Mohamed A, Abdelrehim M, Al-Barazie R. Context matters in machine learning based disease prediction with insights from diverse clinical and symptom data. Scientific Reports 2025;15(1) View
  6. Xu X, Chen H, Wang G, Ding Y. Predictive Value of Machine Learning for Mortality Risk in Acute Pancreatitis. Journal of Clinical Gastroenterology 2025 View
  7. Ameri A, Salmanizadeh F, Samzadeh Kermani H, Ghaemi M. Predicting ADHD in Children and Adolescents With Artificial Intelligence: A Scoping Review of Common Models. Health Science Reports 2025;8(12) View
  8. Liu Y, Oloko-Oba M, Wood K, Lloyd M, Ho J, Hertzberg V. Predicting Atrial Fibrillation Ablation Outcomes: Machine Learning Model Development and Validation Using a Large Administrative Claims Database. JMIR Cardio 2025;9:e77380 View
  9. Zhu C, An J, Zhou L. Neutrophil Percentage–to-Albumin Ratio as a Novel Prognostic Biomarker in Adult Diffuse Gliomas: Retrospective Study Integrating 3 Machine Learning Models and Cox Regression. JMIR Medical Informatics 2026;14:e79945 View
  10. Yang Y, Huang Y, Bai Y, Huang X, Fu Z, Huang Z. Development and validation of a nutrition-integrated nomogram for predicting 28-day mortality in sepsis patients. Frontiers in Nutrition 2026;12 View
  11. Tang Y, Jia L, Zhou J, Dou J, Qian J, Yi X, Soh K. Development of an explainable machine learning model for predicting depression in adults with type 2 diabetes mellitus: A cross-sectional SHAP-based analysis of NHANES 2009–2023. Medicine 2026;105(6):e47522 View

Conference Proceedings

  1. P. S, Das A, Gaurav N, Mishra L, Kanyal P. 2025 International Conference on Sustainable Communication Networks and Application (ICSCN). Healthcare Analytics: Data Mining Techniques on Electronic Health Records (EHR) to Build a Predictive Model for Early Disease Diagnosis View
  2. Septiana V, Hoendarto G, Darmianto A. 2025 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS). Development of a GUI-Based Decision Support System for Stroke Risk Prediction Using DPB-SMOTE and Gradient Boost View
  3. D S, K N P, S R, P S, M D, A S. 2025 4th International Conference on Applied Artificial Intelligence and Computing (ICAAIC). Designing Intelligent and Integrated Analytics Frameworks for Personalized Healthcare View