[HTML][HTML] Deep learning for prediction of depressive symptoms in a large textual dataset

MZ Uddin, KK Dysthe, A F�lstad…�- Neural Computing and�…, 2022 - Springer
Depression is a common illness worldwide with potentially severe implications. Early
identification of depressive symptoms is a crucial first step towards assessment, intervention�…

[HTML][HTML] Deep learning for depression detection from textual data

A Amanat, M Rizwan, AR Javed, M Abdelhaq…�- Electronics, 2022 - mdpi.com
Depression is a prevalent sickness, spreading worldwide with potentially serious
implications. Timely recognition of emotional responses plays a pivotal function at present�…

[HTML][HTML] Automatic depression score estimation with word embedding models

A P�rez, J Parapar, � Barreiro�- Artificial Intelligence in Medicine, 2022 - Elsevier
Depression is one of the most common mental health illnesses. The biggest obstacle lies in
an efficient and early detection of the disorder. Self-report questionnaires are the�…

[HTML][HTML] An hybrid deep learning approach for depression prediction from user tweets using feature-rich CNN and bi-directional LSTM

H Kour, MK Gupta�- Multimedia Tools and Applications, 2022 - Springer
Depression has become one of the most widespread mental health disorders across the
globe. Depression is a state of mind which affects how we think, feel, and act. The number of�…

Predicting depression symptoms in an Arabic psychological forum

NS Alghamdi, HAH Mahmoud, A Abraham…�- IEEE�…, 2020 - ieeexplore.ieee.org
Recently, social media platforms have been widely used as a communication tool on social
networks. Many users have utilized these platforms to reflect their personal lives. These�…

Utilizing neural networks and linguistic metadata for early detection of depression indications in text sequences

M Trotzek, S Koitka, CM Friedrich�- IEEE Transactions on�…, 2018 - ieeexplore.ieee.org
Depression is ranked as the largest contributor to global disability and is also a major
reason for suicide. Still, many individuals suffering from forms of depression are not treated�…

[Retracted] A Novel Text Mining Approach for Mental Health Prediction Using Bi‐LSTM and BERT Model

K Zeberga, M Attique, B Shah, F Ali…�- Computational�…, 2022 - Wiley Online Library
With the current advancement in the Internet, there has been a growing demand for building
intelligent and smart systems that can efficiently address the detection of health‐related�…

Fine-grained depression analysis based on Chinese micro-blog reviews

T Yang, F Li, D Ji, X Liang, T Xie, S Tian, B Li…�- Information Processing &�…, 2021 - Elsevier
Depression is a widespread and intractable problem in modern society, which may lead to
suicide ideation and behavior. Analyzing depression or suicide based on the posts of social�…

Deep learning for depression detection of twitter users

AH Orabi, P Buddhitha, MH Orabi…�- Proceedings of the fifth�…, 2018 - aclanthology.org
Mental illness detection in social media can be considered a complex task, mainly due to the
complicated nature of mental disorders. In recent years, this research area has started to�…

Text-based depression detection on social media posts: A systematic literature review

D William, D Suhartono�- Procedia Computer Science, 2021 - Elsevier
Due to the huge increase of awareness of mental health well-being, the detection of mental
illness itself is starting to become a huge concern. Many psychiatrists found difficulties in�…