Published on in Vol 6, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31615, first published .
Performance of a Computational Phenotyping Algorithm for Sarcoidosis Using Diagnostic Codes in Electronic Medical Records: Case Validation Study From 2 Veterans Affairs Medical Centers

Performance of a Computational Phenotyping Algorithm for Sarcoidosis Using Diagnostic Codes in Electronic Medical Records: Case Validation Study From 2 Veterans Affairs Medical Centers

Performance of a Computational Phenotyping Algorithm for Sarcoidosis Using Diagnostic Codes in Electronic Medical Records: Case Validation Study From 2 Veterans Affairs Medical Centers

Mohamed I Seedahmed   1, 2 , MPH, MD ;   Izabella Mogilnicka   2, 3 , MD ;   Siyang Zeng   2, 4 , MS ;   Gang Luo   4 , PhD ;   Mary A Whooley   2, 5, 6 , MD ;   Charles E McCulloch   7 , PhD ;   Laura Koth   1 * , MD ;   Mehrdad Arjomandi   1, 2 * , MD

1 Division of Pulmonary, Critical Care, Allergy and Immunology, and Sleep, Department of Medicine, University of California San Francisco, San Francisco, CA, United States

2 San Francisco Veterans Affairs Medical Center, San Francisco, CA, United States

3 Department of Experimental Physiology and Pathophysiology, Laboratory of the Centre for Preclinical Research, Medical University of Warsaw, Warsaw, Poland

4 Department of Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Seattle, WA, United States

5 Department of Medicine, University of California San Francisco, San Francisco, CA, United States

6 Measurement Science Quality Enhancement Research Initiative, San Francisco Veterans Affairs Healthcare System, San Francisco, CA, United States

7 Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, United States

*these authors contributed equally

Corresponding Author:

  • Mohamed I Seedahmed, MPH, MD
  • Division of Pulmonary, Critical Care, Allergy and Immunology, and Sleep
  • Department of Medicine
  • University of California San Francisco
  • 513 Parnassus Ave
  • HSE 1314, Box 0111
  • San Francisco, CA, 94143
  • United States
  • Phone: 1 (415) 476 0735
  • Fax: 1 (415) 502 2605
  • Email: mohamed.seedahmed@ucsf.edu