arXiv (All)
open access
PAT: A Personality-Driven Augmentation and Transfer Learning Framework for Depression Detection on Social Media
Depression is a prevalent mental disorder that affects millions worldwide, with early detection crucial for effective intervention. While exist?ing methods have achieved promising results in automated depression detection, they face two key limitations: (1) noise in post screening: symptom-based sem
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
- The Role of Generative AI in Facilitating Social Interactions: A Scoping Review#1014518
- Perinatal Mental Health Detection and Prediction Using Mobile Sensing Data: Systematic Review.#1107521
- HMDF-Net: a transfer learning-based heterogeneous multimodal dynamic fusion network for depression detection among inmates in correctional facilities.#975481
- Passive Smartphone-Based Digital Phenotyping for the Identification of PTSD Symptoms: Initial Validation of a Digital Behavioral Marker#1360303
- Passive Smartphone-Based Digital Phenotyping for the Identification of PTSD Symptoms: Initial Validation of a Digital Behavioral Marker#1360172
Record · ID 1325940
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