Deep learning techniques for suicide and depression detection from online social media: A scoping review

A Malhotra, R Jindal - Applied Soft Computing, 2022 - Elsevier
Psychological health, ie, citizens' emotional and mental well-being, is one of the most
neglected public health issues. Depression is the most common mental health issue and the …

A systematic review of applications of natural language processing and future challenges with special emphasis in text-based emotion detection

S Kusal, S Patil, J Choudrie, K Kotecha, D Vora… - Artificial Intelligence …, 2023 - Springer
Artificial Intelligence (AI) has been used for processing data to make decisions, Interact with
humans, and understand their feelings and emotions. With the advent of the Internet, people …

[HTML][HTML] PHQ-aware depressive symptoms identification with similarity contrastive learning on social media

T Zhang, K Yang, H Alhuzali, B Liu… - Information Processing & …, 2023 - Elsevier
Depressive symptoms identification on social media aims to identify posts from social media
expressing symptoms of depression. This can be beneficial for developing mental health …

A Review on Text-Based Emotion Detection--Techniques, Applications, Datasets, and Future Directions

S Kusal, S Patil, J Choudrie, K Kotecha, D Vora… - arXiv preprint arXiv …, 2022 - arxiv.org
Artificial Intelligence (AI) has been used for processing data to make decisions, interact with
humans, and understand their feelings and emotions. With the advent of the internet, people …

A review on emotion detection by using deep learning techniques

T Chutia, N Baruah - Artificial Intelligence Review, 2024 - Springer
Along with the growth of Internet with its numerous potential applications and diverse fields,
artificial intelligence (AI) and sentiment analysis (SA) have become significant and popular …

A Pilot Study on Clinician-AI Collaboration in Diagnosing Depression from Speech

K Feng, T Chaspari - arXiv preprint arXiv:2410.18297, 2024 - arxiv.org
This study investigates clinicians' perceptions and attitudes toward an assistive artificial
intelligence (AI) system that employs a speech-based explainable ML algorithm for detecting …

Depression detection on social media with user network and engagement features using machine learning methods

AS Liaw, HN Chua - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Depression is a complicated mental health disorder with many different forms and
symptoms. Traditional methods face barriers when detecting and diagnosing depression …

[HTML][HTML] From explainable to interpretable deep learning for natural language processing in healthcare: How far from reality?

G Huang, Y Li, S Jameel, Y Long… - Computational and …, 2024 - Elsevier
Deep learning (DL) has substantially enhanced natural language processing (NLP) in
healthcare research. However, the increasing complexity of DL-based NLP necessitates …

Depression symptoms modelling from social media text: A semi-supervised learning approach

N Farruque, R Goebel, S Sivapalan… - arXiv preprint arXiv …, 2022 - arxiv.org
A fundamental component of user-level social media language based clinical depression
modelling is depression symptoms detection (DSD). Unfortunately, there does not exist any …

Dep-capsule: capsule network for depression detection of Chinese microblog users

R Li, S Wang, Z Sun, A Zhang, Y Luo, X Peng, C Li - Kybernetes, 2024 - emerald.com
Purpose Depression has become one of the most serious and prevalent mental health
problems worldwide. The rise and popularity of social networks such as microblogs provides …