NCBI PubMed Central
open access
Universum Inspired Graph Contrast Learning for Major Depressive Disorder Identification: In Functional Brain Network View.
Background Major depressive disorder (MDD) is a serious psychological disorder marked by persistent feelings of sadness and a notable decline in daily functioning. Functional Brain Networks (FBNs) have become crucial biomarkers for the diagnosis of MDD, and Graph Convolutional Networks (GCNs
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Universum Inspired Graph Contrast Learning for Major Depressive Disorder Identification: In Functional Brain Network View#1052816
- Serotonin Transporter Genetic Variation and Amygdala Responses to Antidepressant Medications in Major Depression#875061
- Altered Inter-Network Functional Integration Underlies Speech Impairment in Parkinson's Disease: A Resting-State fMRI Analysis.#1147166
- Deep learning characterizes depression and suicidal ideation in young adults from eye movements.#220911
- High-Resolution Dynamic Functional Connectivity Generation with Graph-Variate Flow Matching#1132238
Record · ID 1054310
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive