Mental health prediction using machine learning: taxonomy, applications, and challenges
The increase of mental health problems and the need for effective medical health care have
led to an investigation of machine learning that can be applied in mental health problems …
led to an investigation of machine learning that can be applied in mental health problems …
Medical intelligence for anxiety research: Insights from genetics, hormones, implant science, and smart devices with future strategies
This comprehensive review article embarks on an extensive exploration of anxiety research,
navigating a multifaceted landscape that incorporates various disciplines, such as molecular …
navigating a multifaceted landscape that incorporates various disciplines, such as molecular …
[HTML][HTML] Prediction of generalized anxiety levels during the Covid-19 pandemic: A machine learning-based modeling approach
The rapid spread of the Covid-19 outbreak led many countries to enforce precautionary
measures such as complete lockdowns. These lifestyle-altering measures caused a …
measures such as complete lockdowns. These lifestyle-altering measures caused a …
Machine learning-based blood RNA signature for diagnosis of autism spectrum disorder
Early diagnosis of autism spectrum disorder (ASD) is crucial for providing appropriate
treatments and parental guidance from an early age. Yet, ASD diagnosis is a lengthy …
treatments and parental guidance from an early age. Yet, ASD diagnosis is a lengthy …
[HTML][HTML] A hybrid mental health prediction model using Support Vector Machine, Multilayer Perceptron, and Random Forest algorithms
The prevalence and burden of mental health disorders are on the rise in conflict zones, and
if left untreated, they can lead to considerable lifetime disability. Following the repeal of …
if left untreated, they can lead to considerable lifetime disability. Following the repeal of …
Multimodal mental health digital biomarker analysis from remote interviews using facial, vocal, linguistic, and cardiovascular patterns
Objective: Psychiatric evaluation suffers from subjectivity and bias, and is hard to scale due
to intensive professional training requirements. In this work, we investigated whether …
to intensive professional training requirements. In this work, we investigated whether …
[PDF][PDF] Classification of anxiety disorders using machine learning methods: a literature review
This paper focuses on providing a comprehensive literature review on the application of
machine learning algorithms in the diagnosis of anxiety disorder, treatment response, and …
machine learning algorithms in the diagnosis of anxiety disorder, treatment response, and …
A pilot study on AI-driven approaches for classification of mental health disorders
The increasing prevalence of mental disorders among youth worldwide is one of society's
most pressing issues. The proposed methodology introduces an artificial intelligence-based …
most pressing issues. The proposed methodology introduces an artificial intelligence-based …
[HTML][HTML] Machine learning techniques to predict mental health diagnoses: A systematic literature review
Introduction This study aims to investigate the potential of machine learning in predicting
mental health conditions among college students by analyzing existing literature on mental …
mental health conditions among college students by analyzing existing literature on mental …
Understanding importance of clinical biomarkers for diagnosis of anxiety disorders using machine learning models
Anxiety disorders are a group of mental illnesses that cause constant and overwhelming
feelings of anxiety and fear. Excessive anxiety can make an individual avoid work, school …
feelings of anxiety and fear. Excessive anxiety can make an individual avoid work, school …