CalmQuest Using Machine Learning
Himanshu Sorthe1, Jyoti2, Neela Sidar3, Ramesh Bhagat4, Aastha Tiwari5
1B.Tech 8th Sem Student, Computer Science and Engineering, Government Engineering College, Bilaspur, Chhattisgarh, India
2B.Tech 8th Sem Student, Computer Science and Engineering, Government Engineering College, Bilaspur, Chhattisgarh, India
3B.Tech 8th Sem Student, Computer Science and Engineering, Government Engineering College, Bilaspur, Chhattisgarh, India
4B.Tech 8th Sem Student, Computer Science and Engineering, Government Engineering College, Bilaspur, Chhattisgarh, India
5Asst. Professor, Department of Computer Science and Engineering, Government Engineering College, Bilaspur, Chhattisgarh, India
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Abstract - Mental health is a vital aspect of overall well-being, and there are various ways to improve it. A multifaceted approach that involves psychotherapy, mindfulness-based interventions, physical exercise, medication, self-care practices, social support, education, and workplace support can be effective in promoting mental health and well-being. By prioritizing mental health and seeking appropriate support, individuals can lead fulfilling lives and reach their full potential. Prevention and early intervention are crucial to promoting mental health and reducing the negative impact of mental health disorders on individuals, families, and society as a whole.
This project revolves around a dynamic website equipped with a Chabot and a range of multimedia resources to provide accessible and personalized assistance to individuals navigating their mental health journeys. The website serves as a virtual haven, offering a user-friendly interface and intuitive navigation. Upon arrival, visitors are greeted with a warm welcome and guided towards the Survey. The Chabot - an empathetic and knowledgeable companion available 24/7 engages users in meaningful conversations, understanding their concerns, and offering tailored guidance along with valuable mental health resources.
Key Words: Anxiety, Depression, Web Application, Prediction, Sentiment Analysis, Machine Learning, Classification, Random Forest Classifier, Mental Health.