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 …
[HTML][HTML] A multimodal computer-aided diagnostic system for depression relapse prediction using audiovisual cues: A proof of concept
A Othmani, AO Zeghina - Healthcare Analytics, 2022 - Elsevier
Major depressive disorder (MDD), also known as depression, is a common and serious
mental disorder. It is characterized by a high rate of relapse or recurrence where a person …
mental disorder. It is characterized by a high rate of relapse or recurrence where a person …
Automated diagnosis of depression from EEG signals using traditional and deep learning approaches: A comparative analysis
A Khosla, P Khandnor, T Chand - Biocybernetics and Biomedical …, 2022 - Elsevier
Depression is one of the significant contributors to the global burden disease, affecting
nearly 264 million people worldwide along with the increasing rate of suicidal deaths …
nearly 264 million people worldwide along with the increasing rate of suicidal deaths …
A model of normality inspired deep learning framework for depression relapse prediction using audiovisual data
A Othmani, AO Zeghina, M Muzammel - Computer Methods and Programs …, 2022 - Elsevier
Abstract Background: Depression (Major Depressive Disorder) is one of the most common
mental illnesses. According to the World Health Organization, more than 300 million people …
mental illnesses. According to the World Health Organization, more than 300 million people …
[HTML][HTML] Machine learning algorithms for depression: diagnosis, insights, and research directions
Over the years, stress, anxiety, and modern-day fast-paced lifestyles have had immense
psychological effects on people's minds worldwide. The global technological development …
psychological effects on people's minds worldwide. The global technological development …
[HTML][HTML] Scoping review on the multimodal classification of depression and experimental study on existing multimodal models
Depression is a prevalent comorbidity in patients with severe physical disorders, such as
cancer, stroke, and coronary diseases. Although it can significantly impact the course of the …
cancer, stroke, and coronary diseases. Although it can significantly impact the course of the …
[HTML][HTML] Machine learning approaches for diagnosing depression using EEG: A review
Y Liu, C Pu, S Xia, D Deng, X Wang… - Translational Neuroscience, 2022 - degruyter.com
Depression has become one of the most crucial public health issues, threatening the quality
of life of over 300 million people throughout the world. Nevertheless, the clinical diagnosis of …
of life of over 300 million people throughout the world. Nevertheless, the clinical diagnosis of …
Benchmarks for machine learning in depression discrimination using electroencephalography signals
Diagnosis of depression using electroencephalography (EEG) is an emerging field of study.
When mental health facilities are unavailable, the use of EEG as an objective measure for …
When mental health facilities are unavailable, the use of EEG as an objective measure for …
[HTML][HTML] Data mining EEG signals in depression for their diagnostic value
M Mohammadi, F Al-Azab, B Raahemi… - BMC medical informatics …, 2015 - Springer
Background Quantitative electroencephalogram (EEG) is one neuroimaging technique that
has been shown to differentiate patients with major depressive disorder (MDD) and non …
has been shown to differentiate patients with major depressive disorder (MDD) and non …
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 …