Explainable Meta-Learning Ensemble Framework for Predicting Insulin Dose Adjustments in Diabetic Patients: A Comparative Machine Learning Approach with SHAP-Based Clinical Interpretability

<i>Background and Objectives</i>: Diabetes mellitus represents one of the most prevalent chronic metabolic disorders worldwide, necessitating precise insulin dose management to prevent both acute and long-term complications. The optimization of insulin dosing remains a significant clinical challenge...

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Bibliografiset tiedot

Päätekijät:	Emek Guldogan, Burak Yagin, Hasan Ucuzal, Abdulmohsen Algarni, Fahaid Al-Hashem, Mohammadreza Aghaei
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2026-03-01
Sarja:	Medicina
Aiheet:	machine learning ensemble methods insulin dose prediction diabetes mellitus explainable artificial intelligence SHAP
Linkit:	https://www.mdpi.com/1648-9144/62/3/502
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