AN EFFCIET FORCASTING MENTAL HEALTH CONDITION USING MACHINE LEARNING - BABU, Dr. P. BUJJI; JAYALAKSHMI, VISHNUMOLAKALA; HARSHA, PAGADALA NAGA VENKATA SRI; KARTHIK, PALLA; SADHANALA, VENKATA AVINASH (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2024)
Nowadays, people are becoming more and more concerned with their physical health, but mental health is not given the same level of attention. Even if they are aware that they have been afflicted by chronic mental illnesses, many people choose not to seek treatment out of fear of what others would think, a belief that they have lost their minds, a dislike of doctors, or all three. These circumstances make it urgently necessary to find a solution so that more individuals are not inclined to mental diseases. This paper focuses on forecasting mental health using deep learning approaches and machine learning algorithm that is support vector machine. Support vector machine is used to solve the existing problem, as many machine learning and deep learning techniques are helping to solve these contemporary difficulties. SVM gives more accuracy compared to other machine learning algorithms to predict the mental illness.