Interpretation of Depression Detection Models via Feature Selection Methods

Given the prevalence of depression worldwide and its major impact on society, several studies employed artificial intelligence modelling to automatically detect and assess depression. However, interpretation of these models and cues are rarely discussed in detail in the AI community, but have receiv...

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Veröffentlicht in:	IEEE transactions on affective computing 2023-01, Vol.14 (1), p.133-152
Hauptverfasser:	Alghowinem, Sharifa, Gedeon, Tom, Goecke, Roland, Cohn, Jeffrey F., Parker, Gordon
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analytical models Artificial intelligence Australia Biological system modeling Datasets datasets generalisation Deep learning Depression Depression detection Eye movements Feature extraction Feature selection Head movement Linguistics Modelling Motion perception multimodal analysis Speech recognition Stability analysis Yaw
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