Application of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review.

Journal: JMIR research protocols
PMID: 38767948

Abstract

BACKGROUND: Multimorbidity, defined as the coexistence of multiple chronic conditions, poses significant challenges to health care systems on a global scale. It is associated with increased mortality, reduced quality of life, and increased health care costs. The burden of multimorbidity is expected to worsen if no effective intervention is taken. Machine learning has the potential to assist in addressing these challenges since it offers advanced analysis and decision-making capabilities, such as disease prediction, treatment development, and clinical strategies.

Authors

  • Danny Jeganathan Anthonimuthu
    Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark.
  • Ole Hejlesen
    Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
  • Ann-Dorthe Olsen Zwisler
    Clinic for Rehabilitation and Palliative Medicine, Rigshospitalet, Copenhagen, Denmark.
  • Flemming Witt Udsen
    Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark.

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