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

Statistical Methods for Surveillance and Population Health (158) Electronic Health Records (1068) Artificial Intelligence (1421) Machine Learning (1501) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (591) Clinical Information and Decision Making (1434) Innovative Methods in Public Health and Surveillance (336)

Published on in Vol 7, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30824, first published .
Self–Training With Quantile Errors for Multivariate Missing Data Imputation for Regression Problems in Electronic Medical Records: Algorithm Development Study

Self–Training With Quantile Errors for Multivariate Missing Data Imputation for Regression Problems in Electronic Medical Records: Algorithm Development Study

Self–Training With Quantile Errors for Multivariate Missing Data Imputation for Regression Problems in Electronic Medical Records: Algorithm Development Study

Authors of this article:

Hansle Gwon1, 2 Author Orcid Image ;   Imjin Ahn1, 2 Author Orcid Image ;   Yunha Kim1, 2 Author Orcid Image ;   Hee Jun Kang3 Author Orcid Image ;   Hyeram Seo1, 2 Author Orcid Image ;   Ha Na Cho3 Author Orcid Image ;   Heejung Choi1, 2 Author Orcid Image ;   Tae Joon Jun4 Author Orcid Image ;   Young-Hak Kim3 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

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