International Research Journal of Engineering and Technology (IRJET) Volume: 12 Issue: 02 | Feb 2025
www.irjet.net
e-ISSN: 2395-0056 p-ISSN: 2395-0072
Machine Learning in Mental Health: A Web Application for Personalized Assessment and Care Pratiksha Raut1, Sakshi Borse2, Riya Chavan3, Khushi Chavan4, Gayatri Tidke5 1 Assistant Professor, Dept. of Computer Engineering, GES’s R. H. Sapat College of Engineering, Nashik,
Maharashtra, India
2,3,,4,5Student, Dept. of Computer Engineering, GES’s R. H. Sapat College of Engineering, Nashik, Maharashtra, India
---------------------------------------------------------------------***--------------------------------------------------------------------complex mental health data that are now able to identify Abstract - Mental illnesses, such as anxiety, depression, and
cases in early stages and tailor treatments based on patients, which results in better outcomes for the patients. ML techniques like NLP, Decision Trees, and Neural Networks can be applied to a massive amount of data coming from diverse sources like self-reported surveys, wearable devices, and online interactions to look for patterns related to mental health. These techniques enable researchers and health providers to automate assessments, provide real-time insights, and deliver tailored interventions to people in need [2].
stress, are of significant concern all over the world. This study serves an advanced online system called "Mental Health Analysis Using Machine Learning, which predicts mental health conditions by structured questionnaires and machine learning techniques. It makes use of the algorithms of Decision Trees as well as NLP in order to analyze the user inputs and provide suitable personal feedback while also suggesting professional consultation. Predictive analytics, a recommendation engine, progressive tracking, and real-time monitoring of mood would be the system's key features. All information regarding users is encrypted and properly stored for complete data security and privacy. Currently, no one has created anything like Wysa or Woebot. Such a system provides long-term tracking, real-time insights, and personalized recommendations-bridging gaps between selfassessment tools and professional mental health support. Developed using Python, ReactJS, TensorFlow, and MySQL/PostgreSQL, the platform uses Decision Tree algorithms for prediction, collaborative filtering for recommendations, and linear regression for tracking progress. The system is designed to be scalable, user-friendly, and secure. These would include accurate psychometric assessments, early detection of mental health problems, customized recommendations, long-term progress tracking, and professional integration. Other features like gamification and reminders keep the user more engaged and hold onto the user, making this system a full-fledged, accessible mental health support solution.
Mental health issues had been part of human life for thousands of years, even with some historical references that go as far back as the 5th century BC. But in the contemporary world, mental health disorders are now widespread with millions affected globally. Statistics from the Indian government reveal that approximately 130 million people may be suffering from some form of mental illness. Despite these alarming statistics, mental health remains a taboo subject, preventing people from seeking timely medical intervention. According to research, only 8– 10% of the affected population receives proper treatment, while the majority remain undiagnosed and untreated. This lack of awareness and support has led to an increase in suicide rates and increased psychological distress among all sections of society. Primarily, underdeveloped mental health care in India along with other issues such as scarce funding and a lack of mental health professionals is contributing to this crisis. Data by the World Health Organization stipulates that India has only 0.75 psychologists and psychiatrists per 100,000 people whilst countries like Argentina have 106 psychologists per 100,000 people. Another economic constraint prevents millions from accessing mental health care services. A huge portion of the population in India resides below the poverty line and thus does not even have the means to fulfill simple needs like food, shelter, and medical attention, let alone mental health services. Even if they can afford health care, the cost of psychiatric treatment remains a huge challenge. Amongst the most prevalent mental health conditions are depression, anxiety, PTSD, and insomnia. Depression breaks a person's emotions and renders them into constant sadness and despair, while anxiety is described by excessive worrying and nervousness often accompanied by symptoms such as tachycardia and difficulty in breathing. PTSD occurs because of the effects of trauma resulting in
Key Words: User Progress Tracking, Professional Consultation Integration, Recommendation System, Decision Tree Algorithm, Natural Language Processing (NLP).
1. INTRODUCTION Mental health is an important component of well-being, influencing emotions, cognitive functions, and social interactions. Anxiety, depression, and stress are some of the mental illnesses that have severe effects on individuals and society as a whole, making it essential to develop new methods for early detection and intervention. Traditional diagnosis of mental health depends mainly on self-reported assessments using structured questionnaires, which may be subjective and prone to inconsistencies [1]. Advances in technology have brought forward powerful tools to analyze
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