Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46807, first published .
Identification and Prediction of Clinical Phenotypes in Hospitalized Patients With COVID-19: Machine Learning From Medical Records

Identification and Prediction of Clinical Phenotypes in Hospitalized Patients With COVID-19: Machine Learning From Medical Records

Identification and Prediction of Clinical Phenotypes in Hospitalized Patients With COVID-19: Machine Learning From Medical Records

Tom Velez   1 * , PhD, ESQ ;   Tony Wang   2 * , PhD ;   Brian Garibaldi   3 * , MD ;   Eric Singman   4, 5 * , MD, PhD ;   Ioannis Koutroulis   6 * , MBA, MD, PhD

1 Computer Technology Associates, Cardiff, CA, United States

2 Imedacs, Ann Arbor, MI, United States

3 Biocontainment Unit, Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States

4 Department of Ophthalmology and Visual Sciences, University of Maryland School of Medicine, Baltimore, MD, United States

5 Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States

6 Division of Emergency Medicine, Childrens National Hospital, Washington, DC, United States

*all authors contributed equally

Corresponding Author:

  • Eric Singman, MD, PhD
  • Department of Ophthalmology and Visual Sciences
  • University of Maryland School of Medicine
  • 419 W Redwood St, Suite 470
  • Baltimore, MD, 21209
  • United States
  • Phone: 1 443 540 4105
  • Fax: 1 410 328 6503
  • Email: ericsingman@gmail.com