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Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53761, first published .
Application of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review

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

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

Journals

  1. Chen Y, Ji M, Jin L, Dong L, Chen M, Shang X, Lan X, He Y. Risk prediction models for mortality in patients with multimorbidity: a systematic review and meta-analysis. Frontiers in Public Health 2025;13 View
  2. Tonello S, Rolla R, Tillio P, Sainaghi P, Colangelo D. Microenvironment and Tumor Heterogeneity as Pharmacological Targets in Precision Oncology. Pharmaceuticals 2025;18(6):915 View
  3. Anthonimuthu D, Knudsen A, Hejlesen O, Zwisler A, Udsen F. Application of machine learning in multimorbidity research: A scoping review. Journal of Public Health 2025 View
  4. Tsai C, Chang S, Bo Shen T, Lin H, Cheng S, Lee J. Multimorbidity Indices for Adult Population: Systematic Review of Data Framework, Weighting Methods, and Applications. Archives of Gerontology and Geriatrics 2026:106216 View
  5. Alkam T, Tarshizi E, Van Benschoten A. Detecting multimorbidity patterns in Alzheimer's disease using unsupervised machine learning: A nationwide emergency department study (2007–2022). Journal of Alzheimer’s Disease 2026 View