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Machine learning for multimodal mental health detection: a systematic review of passive sensing approaches
As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …
Automatic depression recognition by intelligent speech signal processing: A systematic survey
Depression has become one of the most common mental illnesses in the world. For better
prediction and diagnosis, methods of automatic depression recognition based on speech …
prediction and diagnosis, methods of automatic depression recognition based on speech …
Self-trained deep ordinal regression for end-to-end video anomaly detection
Video anomaly detection is of critical practical importance to a variety of real applications
because it allows human attention to be focused on events that are likely to be of interest, in …
because it allows human attention to be focused on events that are likely to be of interest, in …
Depression detection from social networks data based on machine learning and deep learning techniques: An interrogative survey
Users can interact with one another through social networks (SNs) by exchanging
information, delivering comments, finding new information, and engaging in discussions that …
information, delivering comments, finding new information, and engaging in discussions that …
[PDF][PDF] Detecting Depression with Audio/Text Sequence Modeling of Interviews.
Medical professionals diagnose depression by interpreting the responses of individuals to a
variety of questions, probing lifestyle changes and ongoing thoughts. Like professionals, an …
variety of questions, probing lifestyle changes and ongoing thoughts. Like professionals, an …
A multimodal fusion model with multi-level attention mechanism for depression detection
Depression is a common mental illness that affects the physical and mental health of
hundreds of millions of people around the world. Therefore, designing an efficient and …
hundreds of millions of people around the world. Therefore, designing an efficient and …
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …
to the global burden of disease and intensely influence social and financial welfare of …
[HTML][HTML] Automated depression analysis using convolutional neural networks from speech
To help clinicians to efficiently diagnose the severity of a person's depression, the affective
computing community and the artificial intelligence field have shown a growing interest in …
computing community and the artificial intelligence field have shown a growing interest in …
Automatic assessment of depression based on visual cues: A systematic review
Automatic depression assessment based on visual cues is a rapidly growing research
domain. The present exhaustive review of existing approaches as reported in over sixty …
domain. The present exhaustive review of existing approaches as reported in over sixty …
Artificial intelligent system for automatic depression level analysis through visual and vocal expressions
A human being's cognitive system can be simulated by artificial intelligent systems.
Machines and robots equipped with cognitive capability can automatically recognize a …
Machines and robots equipped with cognitive capability can automatically recognize a …