MindScan: Mental Disorder Diagnosis using Machine Learning
This paper proposes a machine learning-based system for early detection and assessment of mental health issues, enabling timely intervention and support. Moreover, it contributes to reducing the stigma associated with seeking help for psychological concerns by offering a private and non-judgmental digital assessment approach. The paper outlines the system's features, including an intuitive UI, standardized quizzes for various disorders, subjective questions with audio-based answers for enhanced diagnostic accuracy, and an "Attention Monitoring Game" tailored for individuals with ADHD. It integrates counseling resources, information on nearby clinics, and envisions future enhancements such as expanding disorder coverage, improving model accuracy, incorporating hardware-based assessments, and introducing diverse coping strategies. The paper contributes to the advancement in mental health technology, emphasizing the potential of machine learning to revolutionize mental health care and accessibility.
Authors
- Kiran Gawande
- Tisha Negandhi
- Purval Dhumale
- Mishika Vachhani
Publication Details
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/i3ceet61722.2024.10994115
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Education
- Type
- article
- Field-Weighted Citation Impact
- 0.78