Machine Learning in Biomedical Informatics: Optimizing Resource Allocation and Energy Efficiency in Public Hospitals

This paper presents a computational framework that combines supervised machine learning and multi-objective optimization to support data-driven decision-making for resource allocation in public healthcare systems. The study uses real-world data from 51 public hospitals across Southern and Northern I...

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Main Authors: Agostino Marengo, Vito Santamato, Massimo Iacoviello
Formato: Artigo
Idioma:Inglês
Publicado: IEEE 2025-01-01
Series:IEEE Access
Assuntos:
Machine learning
hospital optimization
energy efficiency
multiobjective optimization
SHAP explainability
predictive analytics
Acceso en liña:https://ieeexplore.ieee.org/document/11121831/
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