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

Development and Evaluation of Research Methods, Instruments and Tools (1348) Clinical Information and Decision Making (3759) mHealth in a Clinical Setting (1162) Formative Evaluation of Non-Ehealth Innovations (399)

Published on in Vol 10 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/81039, first published .
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Complication Risk Classification in Children and Adolescents With Type 1 Diabetes: Interpretable Machine Learning Study Based on Saudi Clinical Guidelines

Complication Risk Classification in Children and Adolescents With Type 1 Diabetes: Interpretable Machine Learning Study Based on Saudi Clinical Guidelines

Authors of this article:

Jalilah Fllatah1 Author Orcid Image ;   Haneen Banjar1, 2, 3, 4 Author Orcid Image
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Journals

  1. Wu T, Cai W, Li Z. From explainability to clinical actionability: translating artificial intelligence models into decision support for endocrine disease management. Frontiers in Endocrinology 2026;17 View