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Machine Learning Framework for Identification of Depression

version 1.0.2 (2.71 MB) by Zhifei Li
Identifying Neuroimaging Biomarkers of Major Depressive Disorder from Cortical Hemodynamic Responses Using Machine Learning Approaches

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Updated 25 Sep 2021

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The proposed ML framework involved a sequence process of the fNIRS feature extraction, selection, classification, and validation.
The raw data that support the findings of this study are available on request from the corresponding author (pcmrhcm@nus.edu.sg). The data are not publicly available due to privacy or ethical restrictions.
MATLAB Release Compatibility
Created with R2021b
Compatible with any release
Platform Compatibility
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