Published on in Vol 5, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28620, first published .
A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study

A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study

A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study

Journals

  1. Emerson S, McLinden T, Sereda P, Lima V, Hogg R, Kooij K, Yonkman A, Salters K, Moore D, Toy J, Wong J, Consolacion T, Montaner J, Barrios R, Nicol E. Identification of people with low prevalence diseases in administrative healthcare records: A case study of HIV in British Columbia, Canada. PLOS ONE 2023;18(8):e0290777 View
  2. May S, Giordano T, Gottlieb A. Generalizable pipeline for constructing HIV risk prediction models across electronic health record systems. Journal of the American Medical Informatics Association 2024;31(3):666 View
  3. Pocobelli G, Oliver M, Albertson-Junkans L, Gundersen G, Kamineni A. Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan. BMC Health Services Research 2024;24(1) View
  4. Endebu T, Taye G, Addissie A, Deksisa A, Deressa W. Electronic medical record-based prediction models developed and deployed in the HIV care continuum: a systematic review. Discover Health Systems 2024;3(1) View