Deep learning for depression recognition with audiovisual cues: A review
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 …
pressure, which increases the probability of suffering from depression. However, many …
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 …
Dynamic multimodal measurement of depression severity using deep autoencoding
H Dibeklioğlu, Z Hammal… - IEEE journal of biomedical …, 2017 - ieeexplore.ieee.org
Depression is one of the most common psychiatric disorders worldwide, with over 350
million people affected. Current methods to screen for and assess depression depend …
million people affected. Current methods to screen for and assess depression depend …
End-to-end multimodal clinical depression recognition using deep neural networks: A comparative analysis
M Muzammel, H Salam, A Othmani - Computer Methods and Programs in …, 2021 - Elsevier
Abstract Background and Objective: Major Depressive Disorder is a highly prevalent and
disabling mental health condition. Numerous studies explored multimodal fusion systems …
disabling mental health condition. Numerous studies explored multimodal fusion systems …
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 …
studies employed artificial intelligence modelling to automatically detect and assess …
Detecting depression and predicting its onset using longitudinal symptoms captured by passive sensing: a machine learning approach with robust feature selection
We present a machine learning approach that uses data from smartphones and fitness
trackers of 138 college students to identify students that experienced depressive symptoms …
trackers of 138 college students to identify students that experienced depressive symptoms …
Human behaviour-based automatic depression analysis using hand-crafted statistics and deep learned spectral features
Depression is a serious mental disorder that affects millions of people all over the world.
Traditional clinical diagnosis methods are subjective, complicated and need extensive …
Traditional clinical diagnosis methods are subjective, complicated and need extensive …
Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A …
S Yasin, A Othmani, I Raza, SA Hussain - Computers in Biology and …, 2023 - Elsevier
Mental disorders are rapidly increasing each year and have become a major challenge
affecting the social and financial well-being of individuals. There is a need for phenotypic …
affecting the social and financial well-being of individuals. There is a need for phenotypic …
Multimodal temporal machine learning for Bipolar Disorder and Depression Recognition
F Ceccarelli, M Mahmoud - Pattern Analysis and Applications, 2022 - Springer
Mental disorder is a serious public health concern that affects the life of millions of people
throughout the world. Early diagnosis is essential to ensure timely treatment and to improve …
throughout the world. Early diagnosis is essential to ensure timely treatment and to improve …
[HTML][HTML] Digital phenotyping for differential diagnosis of major depressive episode: narrative review
E Ettore, P Müller, J Hinze, M Riemenschneider… - JMIR mental …, 2023 - mental.jmir.org
Background Major depressive episode (MDE) is a common clinical syndrome. It can be
found in different pathologies such as major depressive disorder (MDD), bipolar disorder …
found in different pathologies such as major depressive disorder (MDD), bipolar disorder …