[HTML][HTML] Deep learning in mental health outcome research: a scoping review
Mental illnesses, such as depression, are highly prevalent and have been shown to impact
an individual's physical health. Recently, artificial intelligence (AI) methods have been …
an individual's physical health. Recently, artificial intelligence (AI) methods have been …
[HTML][HTML] Machine learning for mental health in social media: bibliometric study
Background: Social media platforms provide an easily accessible and time-saving
communication approach for individuals with mental disorders compared to face-to-face …
communication approach for individuals with mental disorders compared to face-to-face …
Predicting anxiety, depression and stress in modern life using machine learning algorithms
In the fast-paced modern world, psychological health issues like anxiety, depression and
stress have become very common among the masses. In this paper, predictions of anxiety …
stress have become very common among the masses. In this paper, predictions of anxiety …
[HTML][HTML] Improving mental health services: A 50-year journey from randomized experiments to artificial intelligence and precision mental health
L Bickman - Administration and Policy in Mental Health and Mental …, 2020 - Springer
This conceptual paper describes the current state of mental health services, identifies critical
problems, and suggests how to solve them. I focus on the potential contributions of artificial …
problems, and suggests how to solve them. I focus on the potential contributions of artificial …
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 …
[HTML][HTML] Detection of suicide ideation in social media forums using deep learning
Suicide ideation expressed in social media has an impact on language usage. Many at-risk
individuals use social forum platforms to discuss their problems or get access to information …
individuals use social forum platforms to discuss their problems or get access to information …
[HTML][HTML] A machine learning approach predicts future risk to suicidal ideation from social media data
Abstract Machine learning analysis of social media data represents a promising way to
capture longitudinal environmental influences contributing to individual risk for suicidal …
capture longitudinal environmental influences contributing to individual risk for suicidal …
[HTML][HTML] Automatic detection of depression symptoms in twitter using multimodal analysis
Depression is the most prevalent mental disorder that can lead to suicide. Due to the
tendency of people to share their thoughts on social platforms, social data contain valuable …
tendency of people to share their thoughts on social platforms, social data contain valuable …
A time-aware transformer based model for suicide ideation detection on social media
Social media's ubiquity fosters a space for users to exhibit suicidal thoughts outside of
traditional clinical settings. Understanding the build-up of such ideation is critical for the …
traditional clinical settings. Understanding the build-up of such ideation is critical for the …
Knowledge-aware assessment of severity of suicide risk for early intervention
Mental health illness such as depression is a significant risk factor for suicide ideation,
behaviors, and attempts. A report by Substance Abuse and Mental Health Services …
behaviors, and attempts. A report by Substance Abuse and Mental Health Services …