Recent neuroimaging advancements have led to datasets characterized by an overwhelming number of features. Different dimensionality reduction techniques have been employed to uncover low-dimensional ...
This study aims to improve survival modeling in head and neck cancer (HNC) by integrating patient-reported outcomes (PROs) using dimensionality reduction techniques. PROs capture symptom severity ...
Hyperspectral imaging generates vast amounts of data containing spatial and spectral information. Dimensionality reduction methods can reduce data size while preserving essential spectral features and ...
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