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...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 25; H. 14; S. 4520
Hauptverfasser:	Zhao, Shiwen, Zhang, Yunze, Su, Yikai, Su, Kaifeng, Liu, Jiemin, Wang, Tao, Yu, Shiqi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 21.07.2025 MDPI
Schlagworte:	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-Zugang:	Volltext
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