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Non-randomized Protocols and Methods (ehealth) (1086) Clinical Information and Decision Making (3646) Electronic Health Records (1700) Methods and Instruments in Medical Informatics (408) Secondary Use of Clinical Data for Research and Surveillance (622) Machine Learning (3123)

Published on in Vol 15 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91647, first published .
Close-up of a human face dissolving into digital pixels, representing AI and data

Computable Phenotype for Identifying Undiagnosed Hypermobile Ehlers-Danlos Syndrome: Protocol for a Development and Validation Study

Computable Phenotype for Identifying Undiagnosed Hypermobile Ehlers-Danlos Syndrome: Protocol for a Development and Validation Study

Authors of this article:

Mohammad Arvan1 Author Orcid Image ;   Rebecca T Feinstein1 Author Orcid Image ;   Nathan J Rudin2 Author Orcid Image ;   Michelle Nichols3 Author Orcid Image
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Mohammad Arvan   1 , PhD ;   Rebecca T Feinstein   1 , MPH, MSW, PhD ;   Nathan J Rudin   2 , MA, MD ;   Michelle Nichols   3 , RN, PhD

1 AI.Health4All Center, College of Medicine, University of Illinois at Chicago, Chicago, IL, United States

2 Department of Orthopedics and Rehabilitation, University of Wisconsin–Madison, Madison, WI, United States

3 Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, United States

Corresponding Author:

  • Michelle Nichols, RN, PhD
  • Department of Health Sciences and Research
  • College of Health Professions, Medical University of South Carolina
  • 77 President Street, MSC 700
  • Charleston, SC 29425
  • United States
  • Phone: 1 843-876-6463
  • Email: nicholmg@musc.edu