Harnessing the Power of Hugging Face Transformers for Predicting Mental Health Disorders in Social Networks
Early diagnosis of mental disorders and intervention can facilitate the prevention of severe injuries and the improvement of treatment results. This study uses social media and pre-trained language models to explore how user-generated data can predict mental disorder symptoms. Our study compares fou...
Saved in:
Main Authors: | Alireza Pourkeyvan, Ramin Safa, Ali Sorourkhah |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10438433/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Apriori algorithm based prediction of students’ mental health risks in the context of artificial intelligence
by: You Fu, et al.
Published: (2025-02-01) -
A Text Mining Approach to Analyzing the Omnichannel Retail Business Performance of the KlikIndomaret App
by: Akhmad Ghiffary Budianto, et al.
Published: (2024-08-01) -
User Analysis of Info BMKG Application in The Perspective of Human Computer Interaction Using Support Vector Machine Algorithm
by: Ilham Fannani, et al.
Published: (2023-06-01) -
BidCorpus: A multifaceted learning dataset for public procurementHugging Face
by: Weslley Lima, et al.
Published: (2025-02-01) -
End-to-end scene text detection and recognition algorithm based on Transformer decoders
by: Jinzhi ZHENG, et al.
Published: (2023-05-01)