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

JMIR Theme Issue: COVID-19 Special Issue (2461) Artificial Intelligence (1427) Clinical Information and Decision Making (1437) Decision Support for Health Professionals (1211) Machine Learning (1504) Infectious Diseases (non-STD/STI) (1594)

Published on in Vol 22, No 12 (2020): December

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/2020.09.18.20197582v1, first published .
Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development

Authors of this article:

Christopher D'Ambrosia1 Author Orcid Image ;   Henrik Christensen1 Author Orcid Image ;   Eliah Aronoff-Spencer2 Author Orcid Image
Article Authors Cited by (5) Tweetations (4) Metrics

Christopher D'Ambrosia   1 , MS ;   Henrik Christensen   1 , PhD ;   Eliah Aronoff-Spencer   2 , MD, PhD

1 Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, United States

2 Division of Infectious Diseases and Global Public Health, School of Medicine, University of California San Diego, San Diego, CA, United States

Corresponding Author:

  • Eliah Aronoff-Spencer, MD, PhD
  • Division of Infectious Diseases and Global Public Health
  • School of Medicine
  • University of California San Diego
  • 9500 Gilman Drive 0711
  • San Diego, CA, 92101
  • United States
  • Phone: 1 6462348153
  • Email: earonoffspencer@health.ucsd.edu