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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


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 ( The data are not publicly available due to privacy or ethical restrictions.
MATLAB Release Compatibility
Created with R2021b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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