AI-Powered Mental Health Diagnosis: A Comprehensive Exploration of Machine and Deep Learning Techniques

Individuals suffering from mental illnesses frequently communicate their sentiments and emotional states on social media through their posts. It is a challenge to recognize individuals suffering from mental health illnesses at an early stage and to provide them with necessary treatment. In this paper, an experimental methodology based on publicly available Reddit data to develop a mental health diagnosis system has been proposed. Natural language processing (NLP) techniques are exploited to help machine understand social media posts from Reddit, and deep learning and machine learning models are trained to classify the social media posts into one of the following four mental illnesses: depression, anxiety, schizophrenia and bipolar. A comparative study of these models' is performed and the results revealed that random forest outperformed other models, by obtaining 90% accuracy. In this study, we also design a web-based platform for deploying the model to aid in diagnosis of mental diseases because people suffering from anxiety or depression refrain from sharing their feelings with doctors, relatives, family, or friends.