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

Electronic Health Records (1269) Gestational Diabetes (40) Machine Learning (1962) Ontologies, Classifications, and Coding (307)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72938, first published .
Label Accuracy in Electronic Health Records and Its Impact on Machine Learning Models for Early Prediction of Gestational Diabetes: 3-Step Retrospective Validation Study

Label Accuracy in Electronic Health Records and Its Impact on Machine Learning Models for Early Prediction of Gestational Diabetes: 3-Step Retrospective Validation Study

Label Accuracy in Electronic Health Records and Its Impact on Machine Learning Models for Early Prediction of Gestational Diabetes: 3-Step Retrospective Validation Study

Authors of this article:

Mark Germaine1, 2 Author Orcid Image ;   Amy C O'Higgins3 Author Orcid Image ;   Brendan Egan2 Author Orcid Image ;   Graham Healy1 Author Orcid Image
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Mark Germaine   1, 2 , PhD ;   Amy C O'Higgins   3 , PhD ;   Brendan Egan   2 , PhD ;   Graham Healy   1 , PhD

1 School of Computing, Dublin City University, Dublin, Ireland

2 School of Health and Human Performance, Dublin City University, Dublin, Ireland

3 UCD (University College Dublin) Centre for Human Reproduction, Coombe Women & Infants University Hospital, Dublin, Ireland

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