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J. , Hejlesen, O. , Zwisler, A.-D. O. , & Udsen, F. W. (2024) . Application of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review. JMIR Research Protocols, 13 , Article e53761 .  \n[https://doi.org/10.2196/53761](https://doi.org/10.2196/53761)  \nGeneral rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  \n-Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  \n-You may not further distribute the material or use it for any profit-making activity or commercial gain  \n-You may freely distribute the URL identifying the publication in the public portal  \nTake down policy  \nIf you believe that this document breaches copyright please contact [us at vbn@aub.aau.dk](us at vbn@aub.aau.dk) providing details, and we will remove access to the work immediately and investigate your claim.  \nDownloaded from [vbn.aau.dk](vbn.aau.dk) on: March 09, 2025  \nJMIR RESEARCH PROTOCOLS Anthonimuthu et al  \nProtocol  \nApplication of Machine Learning in Multimorbidity Research: Protocol for a Scoping Review  \n\n| Danny Jeganathan Anthonimuthu1, MSc; Ole Hejlesen 1, PhD; Ann-Dorthe Olsen Zwisler2,3, PhD; Flemming Witt Udsen 1, PhD |\n| --- |\n| 1Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark 2Clinic for Rehabilitation and Palliative Medicine, Rigshospitalet, Copenhagen, Denmark\u003Cbr>3Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark\u003Cbr>Corresponding Author:\u003Cbr>Danny Jeganathan Anthonimuthu, MSc Department of Health Science and Technology\u003Cbr>Faculty of Medicine Aalborg University Selma Lagerløfs Vej 249 Gistrup, 9260 Denmark\u003Cbr>Phone: 45 41627109\u003Cbr>Email: [dant@hst.aau.dk](dant@hst.aau.dk)\u003Cbr>Abstract |\n| Background: Multimorbidity, defined as the coexistence of multiple chronic conditions, poses significant challenges to healthcare 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.\u003Cbr>Objective: This paper represents the protocol of a scoping review that aims to identify and explore the current literature concerning the use of machine learning for patients with multimorbidity. More precisely, the objective is to recognize various machine learning models, the patient groups involved, features considered, types of input data, the maturity of the machine learning algorithms, and the outcomes from these machine learning models.\u003Cbr>Methods: The scoping review will be based on the guidelines of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) . Five databases (PubMed, Embase, IEEE, Web of Science, and Scopus) are chosen to conduct a literature search. Two reviewers will independently screen the titles, abstracts, and full texts of identified studies based on predefined eli","cbCaidLzVEYazsfA","https://ap.wps.com/l/cbCaidLzVEYazsfA","pdf",356087,"English","# Abstract\n## Background\n## Objective\n## Methods\n## Results\n## Conclusions\n# Introduction","[{\"question\":\"What is the main purpose of the scoping review protocol?\",\"answer\":\"To identify and explore the current literature on the use of machine learning for patients with multimorbidity, including models, patient groups, features, input data, algorithm maturity, and outcomes.\"},{\"question\":\"Which databases and tools are used to conduct and manage the search?\",\"answer\":\"The review uses PubMed, Embase, IEEE, Web of Science, and Scopus, with Covidence for managing and screening papers.\"},{\"question\":\"What study types are included in the scoping review?\",\"answer\":\"Studies that examine more than one chronic disease, or individuals with a single chronic condition at risk of developing another, are included.\"}]","Application of Machine Learning in Multimorbidity Research - Protocol for a Scoping Review | PDF",23]