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

Clinical Informatics (904) Machine Learning (1370) Decision Support for Health Professionals (1127) Electronic Health Records (961) Clinical Information and Decision Making (1314) Secondary Use of Clinical Data for Research and Surveillance (317) Chronic Conditions (213)

Published on in Vol 23, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32900, first published .
Developing the Total Health Profile, a Generalizable Unified Set of Multimorbidity Risk Scores Derived From Machine Learning for Broad Patient Populations: Retrospective Cohort Study

Developing the Total Health Profile, a Generalizable Unified Set of Multimorbidity Risk Scores Derived From Machine Learning for Broad Patient Populations: Retrospective Cohort Study

Developing the Total Health Profile, a Generalizable Unified Set of Multimorbidity Risk Scores Derived From Machine Learning for Broad Patient Populations: Retrospective Cohort Study

Authors of this article:

Abhishaike Mahajan1 Author Orcid Image ;   Andrew Deonarine2 Author Orcid Image ;   Axel Bernal1 Author Orcid Image ;   Genevieve Lyons2 Author Orcid Image ;   Beau Norgeot1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Das A, Dhillon P. Application of machine learning in measurement of ageing and geriatric diseases: a systematic review. BMC Geriatrics 2023;23(1) View
  2. McCracken C, Raisi-Estabragh Z, Szabo L, Veldsman M, Raman B, Topiwala A, Roca-Fernández A, Husain M, Petersen S, Neubauer S, Nichols T. Feasibility of multiorgan risk prediction with routinely collected diagnostics: a prospective cohort study in the UK Biobank. BMJ Evidence-Based Medicine 2024:bmjebm-2023-112518 View