[HTML][HTML] Natural language processing applied to mental illness detection: a narrative review

T Zhang, AM Schoene, S Ji, S Ananiadou - NPJ digital medicine, 2022 - nature.com
Mental illness is highly prevalent nowadays, constituting a major cause of distress in
people's life with impact on society's health and well-being. Mental illness is a complex multi …

Deep facial expression recognition: A survey

S Li, W Deng - IEEE transactions on affective computing, 2020 - ieeexplore.ieee.org
With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

Facebook language predicts depression in medical records

JC Eichstaedt, RJ Smith… - Proceedings of the …, 2018 - National Acad Sciences
Depression, the most prevalent mental illness, is underdiagnosed and undertreated,
highlighting the need to extend the scope of current screening methods. Here, we use …

Automated assessment of psychiatric disorders using speech: A systematic review

DM Low, KH Bentley, SS Ghosh - Laryngoscope investigative …, 2020 - Wiley Online Library
Objective There are many barriers to accessing mental health assessments including cost
and stigma. Even when individuals receive professional care, assessments are intermittent …

AVEC 2019 workshop and challenge: state-of-mind, detecting depression with AI, and cross-cultural affect recognition

F Ringeval, B Schuller, M Valstar, N Cummins… - Proceedings of the 9th …, 2019 - dl.acm.org
The Audio/Visual Emotion Challenge and Workshop (AVEC 2019)'State-of-Mind, Detecting
Depression with AI, and Cross-cultural Affect Recognition'is the ninth competition event …

Estimation of continuous valence and arousal levels from faces in naturalistic conditions

A Toisoul, J Kossaifi, A Bulat, G Tzimiropoulos… - Nature Machine …, 2021 - nature.com
Facial affect analysis aims to create new types of human–computer interactions by enabling
computers to better understand a person's emotional state in order to provide ad hoc help …

Deep learning for depression recognition with audiovisual cues: A review

L He, M Niu, P Tiwari, P Marttinen, R Su, J Jiang… - Information …, 2022 - Elsevier
With the acceleration of the pace of work and life, people are facing more and more
pressure, which increases the probability of suffering from depression. However, many …

Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architectures, and beyond

D Kollias, P Tzirakis, MA Nicolaou… - International Journal of …, 2019 - Springer
Automatic understanding of human affect using visual signals is of great importance in
everyday human–machine interactions. Appraising human emotional states, behaviors and …

MFCC-based recurrent neural network for automatic clinical depression recognition and assessment from speech

E Rejaibi, A Komaty, F Meriaudeau, S Agrebi… - … Signal Processing and …, 2022 - Elsevier
Abstract Clinical depression or Major Depressive Disorder (MDD) is a common and serious
medical illness. In this paper, a deep Recurrent Neural Network-based framework is …

Mer 2023: Multi-label learning, modality robustness, and semi-supervised learning

Z Lian, H Sun, L Sun, K Chen, M Xu, K Wang… - Proceedings of the 31st …, 2023 - dl.acm.org
The first Multimodal Emotion Recognition Challenge (MER 2023) 1 was successfully held at
ACM Multimedia. The challenge focuses on system robustness and consists of three distinct …