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

Artificial Intelligence (5107) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3413) Telehealth and Telemonitoring (3184) Electronic Health Records (1813) Ontologies, Classifications, and Coding (479) Machine Learning (3379) Artificial Intelligence in Industry (54) AI Data (43) Applications of AI (1131)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77893, first published .
Healthcare professional using laptop with digital medical data visualization

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 (3) Tweetations Metrics

Journals

  1. Huet-Dastarac M, Dankar F, Liu D, El Kababji S, Pilgram L, El Emam K. An Evaluation of Pretrained Generative Models for Augmenting Small Health Data: Comparative Modeling Study. Journal of Medical Internet Research 2026;28:e88678 View
  2. Thees O, Müller R, Templ M. Beyond the Trade-Off Curve: Multivariate and Advanced Risk-Utility Maps for Evaluating Anonymized Data. Journal of Official Statistics 2026 View
  3. Venerito V, Morrone M, Del Vescovo S, Bilgin E, Gupta L, Lopalco G, Iannone F. Synthetic data in rheumatology: a systematic literature review. Rheumatology Advances in Practice 2026;10(4) View