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

Formative Evaluation of Digital Health Interventions (5255) Tools, Programs and Algorithms (594) Imaging Informatics (481) Machine Learning (3273) Data Science (715) Research Methodology - AI (190) Applications of AI (1023)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91492, first published .
Futuristic MRI scanner with glowing interior and patient bed

Automated Machine Learning Frameworks for Radiomics: Comparative Evaluation Study

Automated Machine Learning Frameworks for Radiomics: Comparative Evaluation Study

Authors of this article:

Jose Lozano-Montoya1, 2 Author Orcid Image ;   Emilio Soria-Olivas3 Author Orcid Image ;   Almudena Fuster-Matanzo2 Author Orcid Image ;   Angel Alberich-Bayarri2 Author Orcid Image ;   Ana Jimenez-Pastor2 Author Orcid Image
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Journals

  1. Hamdan M, Badr Z, Uribe S, Reymus M, Kalenderian E, Schwendicke F. No-Code and Low-Code Artificial Intelligence in Healthcare Imaging: A Scoping Review. International Dental Journal 2026;76(6):109797 View