DepressionMIGNN: A Multiple-Instance Learning-Based Depression Detection Model with Graph Neural Networks

The global prevalence of depression necessitates the application of technological solutions, particularly sensor-based systems, to augment scarce resources for early diagnostic purposes. In this study, we use benchmark datasets that contain multimodal data including video, audio, and transcribed tex...

Full description

Saved in:

Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 25; no. 14; p. 4520
Main Authors:	Zhao, Shiwen, Zhang, Yunze, Su, Yikai, Su, Kaifeng, Liu, Jiemin, Wang, Tao, Yu, Shiqi
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 21.07.2025 MDPI
Subjects:	Algorithms Artificial intelligence Comparative analysis Computer-aided medical diagnosis Data processing Depression - diagnosis depression recognition Depression, Mental Diagnosis Graph Neural Networks Human acts Human behavior Humans Identification and classification Mental depression Mental disorders Mental health care Methods multi-dimensional edge multimodality Multiple-Instance Learning Algorithms Neural networks Neural Networks, Computer China graph neural networks multimodality depression recognition multi-dimensional edge
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!