Leveraging Artificial Intelligence for Psychometric Assessment in Mental Health

AIPAMH
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Objectives
  1. Design AI-Based Frameworks for Psychometric Assessment in Mental Health.
  2. Develop and Optimize AI Models for Early Detection and Prevention of Mental Health Conditions.
  3. Harnessing Multimodal Data for Mental Health Profiling.
  4. Leveraging Explainable AI to analyze Performance of Proposed AI Frameworks.
  5. Deploy AI Systems for Continuous Monitoring and Real-Time Feedback.

 

Issues Involved

Mental health disorders are a growing global concern, affecting individuals across all demographics. Despite advances in understanding mental health, challenges persist in accurate diagnosis, early detection, and effective intervention. Traditional psychometric assessments are limited by subjectivity, lack of scalability, and delayed intervention. This issue is exacerbated by the complexity of mental health, which involves multifaceted and dynamic factors that traditional tools fail to capture. There is a need for AI-based frameworks capable of leveraging multimodal data for accurate and early detection, providing continuous monitoring, and ensuring explainability to foster trust and adoption.

 

Team Lead

Dr Preeti Gupta

preeti.gupta@nmims.edu


Team Members

  1. Name: Shailendra Aote

Email ID:shailendra.aote@nmims.edu

  1. Name: Sakshi Indolia

Email ID:sakshi.indolia@nmims.edu

  1. Name: Dr Preeti Agarwal

Email ID:preeti.agarwal@nmims.edu