PubMed
open access
Enhancing explainability and performance of the depression detection model on social media utilizing feature engineering and LLMs.
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
- Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity#785085
- Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity#783495
- Interpretable Symptom Vectors for Depression in a Large Language Model#822255
- Early Depression Detection in Social Media: Monitoring of Individual Nighttime Dynamics and Large Language Model Analysis.#281119
- Building an early warning model for the risk of suicide attempt in people with depression based on machine learning: a single-centre study.#610510
Record · ID 9997
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