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

Formative Evaluation of Digital Health Interventions (5514) Clinical Information and Decision Making (3987) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (291) Machine Learning (3406) Artificial Intelligence (5155) Chemotherapy and Side Effects Management (153)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67767, first published .
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Web-Based Explainable Machine Learning-Based Drug Surveillance for Predicting Sunitinib- and Sorafenib-Associated Thyroid Dysfunction: Model Development and Validation Study

Web-Based Explainable Machine Learning-Based Drug Surveillance for Predicting Sunitinib- and Sorafenib-Associated Thyroid Dysfunction: Model Development and Validation Study

Authors of this article:

Fan-Ying Chan1 Author Orcid Image ;   Yi-En Ku1 Author Orcid Image ;   Wen-Nung Lie2 Author Orcid Image ;   Hsiang-Yin Chen1, 3 Author Orcid Image
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  3. Jheng S, Chan F, Chang F, Cheng J, Chen H. Predicting lithium-associated thyroid dysfunction through dimension reduction to establish a practical machine learning model: A retrospective multicenter study. Journal of Affective Disorders 2026;405:121633 View
  4. Su Z, Wang S, Wang X, Yao W, Li Y, Wang H, Wang J, Jia M. Application of artificial intelligence in the diagnosis and treatment of thyroid cancer. Frontiers in Endocrinology 2026;17 View