[HTML][HTML] Natural language processing applied to mental illness detection: a narrative review
Mental illness is highly prevalent nowadays, constituting a major cause of distress in
people's life with impact on society's health and well-being. Mental illness is a complex multi …
people's life with impact on society's health and well-being. Mental illness is a complex multi …
Deep learning techniques for suicide and depression detection from online social media: A sco** review
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 …
neglected public health issues. Depression is the most common mental health issue and the …
A textual-based featuring approach for depression detection using machine learning classifiers and social media texts
Depression is one of the leading causes of suicide worldwide. However, a large percentage
of cases of depression go undiagnosed and, thus, untreated. Previous studies have found …
of cases of depression go undiagnosed and, thus, untreated. Previous studies have found …
Self-trained deep ordinal regression for end-to-end video anomaly detection
Video anomaly detection is of critical practical importance to a variety of real applications
because it allows human attention to be focused on events that are likely to be of interest, in …
because it allows human attention to be focused on events that are likely to be of interest, in …
Mental health analysis in social media posts: a survey
M Garg - Archives of Computational Methods in Engineering, 2023 - Springer
The surge in internet use to express personal thoughts and beliefs makes it increasingly
feasible for the social NLP research community to find and validate associations between …
feasible for the social NLP research community to find and validate associations between …
Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media
The ability to explain why the model produced results in such a way is an important problem,
especially in the medical domain. Model explainability is important for building trust by …
especially in the medical domain. Model explainability is important for building trust by …
Depression detection from social networks data based on machine learning and deep learning techniques: An interrogative survey
KM Hasib, MR Islam, S Sakib, MA Akbar… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Users can interact with one another through social networks (SNs) by exchanging
information, delivering comments, finding new information, and engaging in discussions that …
information, delivering comments, finding new information, and engaging in discussions that …
Towards interpretable mental health analysis with large language models
A survey of transformer-based multimodal pre-trained modals
With the broad industrialization of Artificial Intelligence (AI), we observe a large fraction of
real-world AI applications are multimodal in nature in terms of relevant data and ways of …
real-world AI applications are multimodal in nature in terms of relevant data and ways of …