A Short Review on Diagnosing and Predicting Mental Disorders with Machine Learning

Abstract

Mental disorders like schizophrenia, anxiety, and depression impact millions worldwide, requiring early detection and accurate diagnosis. This paper reviews the use of machine learning (ML) in mental health, analyzing data from social media, neuroimaging, EEG, and surveys. ML models achieve high accuracy in detecting schizophrenia, anxiety, and depression, offering scalable and personalized solutions. Challenges include data privacy, diversity, and model interpretability, but advances in explainable AI and multimodal integration address these issues. This study highlights ML's potential to revolutionize mental health care through innovative and accessible technologies.

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