Al-Driven Detection and Analysis of Mental Disorders: An Integrative Review of Machine Learning and Deep Learning Methodologies

Machine Learning-Driven Mental Health Detection: A Comparative Analysis of Existing Techniques and Development of a Predictive Computational Model

A novel machine learning-driven predictive computational model based on DistilBERT for automated multi-class mental health identification from Reddit posts is proposed in this paper and indicates that transformer-based models are robust and scalable solutions for real-world mental health testing and decision-support sy...

An Enhanced Deep Learning Framework Integrating Adaptive Whale Optimization and Natural Language Processing for Mental Health Disorder Diagnosis

Mental health disorders are among the biggest global public health challenges, affecting over 1 billion people worldwide and placing a burden on healthcare systems, economies, and societies. Despite progress in clinical psychiatry, mental health professionals still rely heavily on subjective judgments to make diagnoses...

THE APPLICATION OF MACHINE LEARNING IN EARLY DETECTION OF MENTAL HEALTH CONDITIONS THROUGH ANALYSIS OF HEALTHCARE CLAIMS DATA

Mental illness is a major world health issue, with increasing rates of depression, anxiety, and other psychiatric disorders affecting millions of people worldwide. Early diagnosis is crucial in preventing violent presentation and maximizing patient outcomes. However, conventional diagnosis largely relies on self-report...

Machine Learning Modelling of Mental Disorders in the People of South Sudan

The increase in mental health challenges among the population has raised serious concerns among educators, healthcare professionals, and lawmakers. Because of the substantial impact of mental diseases on emotions, cognition, and social relationships, creative preventative and intervention measures are required, particu...

Identifying Mental Health Conditions in Cancer Patients Using a Hybrid TCN-BiGRU-DATT Deep Learning Model

Cancer patients suffer a tremendous psychological burden, but a substantial portion of that is not captured in the clinic due to the episodic nature of screening and reliance on disclosure. Social media text can be a valuable tool for identifying mental health issues as many patients are able to communicate their fears...

Explainable AI for Mental Disorder Detection on Social Media: A Survey and Outlook