Self Identifying Mental Health Status and Get Guidance For Support Using AI

In recent years, an awareness has emerged about the importance of the individual in mental health and treatment. Mental health problems are common among college students around the world; Therefore, identifying at-risk groups will help provide services. Self-diagnosis of mental illness is an important step in recognizing and addressing personal health. Our goal is to develop a screening tool to identify students at risk for mental illness. Students are taught to use assessment tools to distinguish between those at reduced and increased risk of mental illness. Psychological services should be provided to students at risk. Despite the prevalence of psychological problems, problems such as fear of decision-making and lack of information often make it difficult for people to define themselves. The person may deny or ignore symptoms, which may delay the person's intervention and make the situation worse. Empowering people with mental health knowledge and resources can enable them to take part in their own health. As well as personal benefits, self-expression can promote understanding and acceptance and contribute to a culture of empathy and support. Artificial Intelligence (AI) technology holds both great promise and potential pitfalls in transforming mental health. This article discusses the current limitations of artificial intelligence, areas where further research is needed, and how it can improve healthcare by considering the ethical fairness of intellectual technology. As AI technology continues to evolve and improve, it may be able to help psychiatrists reclassify mental disorders beyond what is currently specified in the DSM-5, identifying these problems in their early or prodromal stages so that interventions can be implemented. . Quality and personalized treatment based on individual characteristics. However, caution must be exercised to avoid overinterpretation of preliminary results, and more studies must be conducted to close the gap in scientific expertise on mental health and treatment.