• Chandan Jaiswal
• Samiksha Shetty
• Janvi Sureja
• Omkar Walunj
• Anas Dange

Over the last few decades, psychological health issues have become very common in people worldwide. The World Health Organization (WHO) has observed that depression is the most prevalent mental disorder affecting more than 300 million people worldwide, and the severity of the issue has led many health researchers to focus their studies in this area. Differentiating anxiety, depression and stress from one another is problematic for machines; hence an appropriate learning algorithm is required for an accurate diagnosis. According to WHO, a healthy person possesses a healthy brain along with physical wellness. In this project, prediction of the occurrence of psychological problems such as anxiety, depression and stress will be made by applying various machine learning algorithms to data taken from the online Depression, Anxiety and Stress Scale (DASS21) tool. The prediction of stress and other mental illnesses isn’t enough. So, we are proposing a system which predicts these factors and also provides relief techniques for different severity levels.

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"AI FOR MENTAL HEALTH", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.f197-f202, April-2022, Available :http://www.jetir.org/papers/JETIR2204527.pdf

"AI FOR MENTAL HEALTH", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppf197-f202, April-2022, Available at : http://www.jetir.org/papers/JETIR2204527.pdf