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

Journal: JMIR medical informatics
Published Date: Jun 19, 2025

Abstract

BACKGROUND: Machine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. With the increasing availability of real-world data (RWD) from diverse sources, such as electronic health records (EHRs), patient registries, and wearable devices, ML techniques present substantial potential to enhance clinical outcomes. Despite this promise, challenges such as data quality, model transparency, generalizability, and integration into clinical practice persist.

Authors

  • Norah Hamad Alhumaidi
    College of Medicine, Qassim University, Buraidah, Saudi Arabia.
  • Doni Dermawan
    Applied Biotechnology, Faculty of Chemistry, Warsaw University of Technology, Warsaw, Poland.
  • Hanin Farhana Kamaruzaman
    Malaysian Health Technology Assessment Section, Medical Development Division, Ministry of Health Malaysia, Wilayah Persekutuan Putrajaya, Malaysia.
  • Nasser Alotaiq
    Health Sciences Research Center, Imam Mohammad ibn Saud Islamic University, Riyadh, Saudi Arabia.

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