Machine learning for multimodal mental health detection: a systematic review of passive sensing approaches

LS Khoo, MK Lim, CY Chong, R McNaney - Sensors, 2024 - mdpi.com
As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

[Retracted] Psychological Analysis for Depression Detection from Social Networking Sites

S Gupta, L Goel, A Singh, A Prasad… - Computational …, 2022 - Wiley Online Library
Rapid technological advancements are altering people's communication styles. With the
growth of the Internet, social networks (Twitter, Facebook, Telegram, and Instagram) have …

[HTML][HTML] Construction of an emotional lexicon of patients with breast cancer: development and sentiment analysis

C Li, J Fu, J Lai, L Sun, C Zhou, W Li, B Jian… - Journal of Medical …, 2023 - jmir.org
Background The innovative method of sentiment analysis based on an emotional lexicon
shows prominent advantages in capturing emotional information, such as individual …

Development of a prediction model for the depression level of the elderly in low-income households: Using decision trees, logistic regression, neural networks, and …

KM Kim, JH Kim, HS Rhee, BY Youn - Scientific reports, 2023 - nature.com
Korea is showing the fastest trend in the world in population aging; there is a high interest in
the elderly population nationwide. Among the common chronic diseases, the elderly tends to …

CAIINET: Neural network based on contextual attention and information interaction mechanism for depression detection

L Zhou, Z Liu, X Yuan, Z Shangguan, Y Li, B Hu - Digital Signal Processing, 2023 - Elsevier
Depression is a globally widespread psychological disorder that has a serious impact on the
physical and mental health of patients. Currently, depression detection methods based on …

Depression detection on social media with the aid of machine learning platform: A comprehensive survey

GK Gupta, DK Sharma - 2021 8th International Conference on …, 2021 - ieeexplore.ieee.org
Depression is a group of mental disorders associated with certain factors which can affect
the mood, feelings, negativity, losing interest, and sadness in human participants. To …

A BERT-Based Summarization approach for depression detection

HS Gavalan, MN Rastgoo, B Nakisa - arXiv preprint arXiv:2409.08483, 2024 - arxiv.org
Depression is a globally prevalent mental disorder with potentially severe repercussions if
not addressed, especially in individuals with recurrent episodes. Prior research has shown …

Chinese MentalBERT: Domain-Adaptive Pre-training on Social Media for Chinese Mental Health Text Analysis

W Zhai, H Qi, Q Zhao, J Li, Z Wang, H Wang… - arXiv preprint arXiv …, 2024 - arxiv.org
In the current environment, psychological issues are prevalent and widespread, with social
media serving as a key outlet for individuals to share their feelings. This results in the …

Behavioral and electrophysiological analyses of self-referential neural processing in major depressive disorder

P Liu, Y Zhao, H Fan, Y Wu, L Liu, J Zhang, D Li… - Asian Journal of …, 2023 - Elsevier
Cognitive theories suggest that patients with major depressive disorder (MDD) constantly
negatively evaluate their self-referential information. Unlike Westerners with an independent …

New chaos-integrated improved grey wolf optimization based models for automatic detection of depression in online social media and networks

S Akyol - PeerJ Computer Science, 2023 - peerj.com
Depression is a psychological effect of the modern lifestyle on people's thoughts. It is a
serious individual and social health problem due to the risk of suicide and loss of workforce …