Published on in Vol 6, No 3 (2022): March
![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](https://asset.jmir.pub/assets/54ef7bb72245fc2571d2c412bd782b1e.png 480w,https://asset.jmir.pub/assets/54ef7bb72245fc2571d2c412bd782b1e.png 960w,https://asset.jmir.pub/assets/54ef7bb72245fc2571d2c412bd782b1e.png 1920w,https://asset.jmir.pub/assets/54ef7bb72245fc2571d2c412bd782b1e.png 2500w)
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