mHealth hyperspectral learning for instantaneous spatiospectral imaging of hemodynamics

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B), hyperspectral data in a subarea are directly fed into the tissue reflectance spectral model to compute the hemodynamic parameters within the same subarea. The obtained data set serves to train a deep neural network that computes the hemodynamic parameters with RGB values as an input.

Importantly, deep learning informed by hyperspectral information is advantageous for designing explainable and interpretable neural networks. Among similar yet distinct terms, such as understandability and comprehensibility (

 

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