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

Artificial Intelligence (2078) AI Data (19) Machine Learning (2042) Applications of AI (274) Artificial Intelligence in Industry (12) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2074) Telehealth and Telemonitoring (2060) Electronic Health Records (1297) Ontologies, Classifications, and Coding (319)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77893, first published .
Magnitude and Impact of Hallucinations in Tabular Synthetic Health Data on Prognostic Machine Learning Models: Validation Study

Magnitude and Impact of Hallucinations in Tabular Synthetic Health Data on Prognostic Machine Learning Models: Validation Study

Magnitude and Impact of Hallucinations in Tabular Synthetic Health Data on Prognostic Machine Learning Models: Validation Study

Authors of this article:

Lisa Pilgram1, 2, 3 Author Orcid Image ;   Samer El Kababji2 Author Orcid Image ;   Dan Liu1, 2 Author Orcid Image ;   Khaled El Emam1, 2 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Lisa Pilgram   1, 2, 3 , MD ;   Samer El Kababji   2 , PhD ;   Dan Liu   1, 2 , PhD ;   Khaled El Emam   1, 2 , PhD

1 School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada

2 CHEO Research Institute, Children's Hospital of Eastern Ontario, Ottawa, ON, Canada

3 Department of Nephrology and Medical Intensive Care, Charité - Universitaetsmedizin Berlin, Berlin, Germany

Corresponding Author: