Can Unsupervised Machine Learning Support Malnutrition Risk Screening in Older Adults? A Preliminary Study Using Multidimensional Phenotyping and Hierarchical Clustering on Principal Components.

Abstract excerpt

Background/Objectives: Malnutrition in older adults constitutes a significant public health concern, reflecting a multifactorial risk and demonstrating the necessity of early identification in geriatric care. This preliminary study aimed to explore whether an unsupervised machine learning (ML) approach based on hierarchical clustering on principal components (HCPC) could help characterize multidimensional...

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