![]() ![]() Features are selected separately from correlation and network characteristics using Minimum Redundancy Maximum Relevance (mRMR) to create the final classifier. Mean time-series for each of the frequency bands are utilized to compute the Pearson correlation and network characteristics. ![]() For each subject, mean time-series are extracted from 85 brain regions and they are decomposed to 4-frequency bands. This paper explores the use of resting-state functional connectivity and network features to classify MDD vs. Discovering quantifiable signals and biomarkers associated with MDD using functional magnetic resonance imaging (fMRI) scans of patients have the potential to assist the clinicians in their assessment. However, diagnosing MDD requires the clinicians to personally interview the subjects and rate the symptoms based on Diagnostic and Statistical Manual of Mental Disorders (DSM), which can be very time consuming. Accurate diagnosis of this disorder is necessary for planning individualized treatment. Keywords: Neurological disorders - Psychiatric disordersĪbstract: Major Depressive Disorder (MDD) is a very serious mental illness that can affect the daily lives of patients. ![]()
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