Mental Health Assessment using AI with Sentiment Analysis and NLP

Abstract

An Artificial Intelligence (AI) based mental health assessment that has the potential to take input from users and classify into two groups: 0 or 1 based on the training dataset. AI has the potential to revolutionize mental health assessment by providing a more accurate and efficient diagnosis, improving treatment outcomes, and increasing access to mental health services. One of the most common is through the use of machine learning algorithms. Which is used to identify patterns and predict mental health conditions. Another way in which AI can be used in mental health assessment is through the analysis of speech and language patterns. Natural Language Processing (NLP) algorithm scan be used to analyze written or spoken language to detect patterns that may indicate mental health conditions such as depression, anxiety, or schizophrenia. We want to report clients facing mental health issues directly to doctors in case of a high-profile illness or suggest a suitable course of action to calm the client without intimating the client of the results unless positive. The critical shortage of psychiatrists and other mental health specialists to provide treatment increases the crisis of untreated mental health conditions. Those who can undergo treatment often forgo it as it is too expensive. Thus, we will use AI to screen, diagnose and treat mental illnesses at a fraction /free of cost.