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

Journals

  1. Seedahmed M, Baugh A, Albirair M, Luo Y, Chen J, McCulloch C, Whooley M, Koth L, Arjomandi M. Epidemiology of Sarcoidosis in U.S. Veterans from 2003 to 2019. Annals of the American Thoracic Society 2023;20(6):797 View
  2. Xia E, Gaurav A, Noe M, Mostaghimi A, Imadojemu S. Validation of the Diagnostic Code for Cutaneous Sarcoidosis in an Electronic Health Database: A Cross-Sectional Analysis. Journal of Investigative Dermatology 2024;144(10):2308 View
  3. Rivera N. Big data in sarcoidosis. Current Opinion in Pulmonary Medicine 2024;30(5):561 View
  4. Masison J, Lehmann H, Wan J. Utilization of Computable Phenotypes in Electronic Health Record Research: A Review and Case Study in Atopic Dermatitis. Journal of Investigative Dermatology 2024 View