MindMap: A Review on Mental Health Analysis using ML

Mental stress on both teachers & students is a significant concern in today’s fast-paced and demanding educational environment. Both of them face academic pressure in their own set of way, students have intense competition in academics whereas teachers are often evaluated based on their student’s performance. Other examples creating mental stress are workload, social pressure, lack of support from parents in student’s case or higher authorities in teacher’s case, mental health stigma. In India people really don’t take care of their mental health or visit a psychiatrist due to the fear of people’s judgement, hence an application for analyzing mental health is great method to detect mental health issues. Accessibility: These tools are typically accessible anytime and anywhere, making mental health resources available to a wide audience. Particularly accommodating for those who may not have simply get to conventional mental wellbeing administrations. Anonymity: Some users may feel more comfortable sharing their thoughts and feelings with an app rather than a human. The anonymity of these apps can encourage individuals to open up and seek help. In this information driven world there’s a part of progression in databased instruments which can analyze the information can be utilized to think about mental wellbeing of a individual utilizing machine learning calculation. Machine learning calculations are classified into classification and clustering where a combination of both could be an important expansion to discover around the mental state of a specific individual. Algorithms like SVM, KNN, K-means Clustering, & classification algorithms.