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

Methods and Instruments in Medical Informatics (186) Machine Learning (2049) Electronic Health Records (1302) Secondary Use of Clinical Data for Research and Surveillance (469) Tools, Programs and Algorithms (373) New Methods (1127)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79307, first published .
Methods for Addressing Missingness in Electronic Health Record Data for Clinical Prediction Models: Comparative Evaluation

Methods for Addressing Missingness in Electronic Health Record Data for Clinical Prediction Models: Comparative Evaluation

Methods for Addressing Missingness in Electronic Health Record Data for Clinical Prediction Models: Comparative Evaluation

Authors of this article:

Jean Digitale1, 2 Author Orcid Image ;   Deborah Franzon3 Author Orcid Image ;   Mark J Pletcher2 Author Orcid Image ;   Charles E McCulloch2 Author Orcid Image ;   Efstathios D Gennatas2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Jean Digitale   1, 2 , PhD, MPH, BSN ;   Deborah Franzon   3 , MD ;   Mark J Pletcher   2 , MD, MPH ;   Charles E McCulloch   2 , PhD ;   Efstathios D Gennatas   2 , MBBS, PhD

1 National Clinician Scholars Program, University of California, San Francisco, San Francisco, CA, United States

2 Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States

3 Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, San Francisco, CA, United States

Corresponding Author:

  • Jean Digitale, PhD, MPH, BSN
  • Department of Epidemiology and Biostatistics
  • University of California, San Francisco
  • 550 16th St, 2nd Floor
  • San Francisco, CA 94158
  • United States
  • Phone: 1 (415) 476-2300
  • Email: jean.digitale@ucsf.edu