National Center for Measurement and Assurance of Trustworthiness, Privacy and Security of Medical AI Systems

Making Medical AI Safe for India.

We are building the national foundation to measure, evaluate, and ensure that AI systems used in Indian healthcare are trustworthy, fair, and secure.

AI is scaling fast.
Evaluation is not.

Artificial Intelligence is rapidly entering Indian hospitals and public health programs. But a crucial question remains unanswered: How do we know these systems are safe?

Current standards only measure accuracy. They fail to test for hidden biases, data leaks, and dangerous "hallucinations" that occur when AI faces real-world Indian clinical environments.

Privacy Risks

Medical AI can unintentionally memorize and leak sensitive patient data.

Hidden Bias

Systems trained on narrow data can underdiagnose marginalized populations.

Clinical Hallucinations

AI often invents highly confident, yet completely fabricated medical advice.

What we test.

We evaluate multimodal AI systems (text, imaging, speech, and video) across four critical pillars of trustworthiness before they reach the patient.

Security & Privacy

Subjecting models to rigorous stress tests to ensure they resist adversarial attacks and comply strictly with the Digital Personal Data Protection (DPDP) Act.

Fairness & Equity

Auditing systems across age, gender, language, and geography to expose disparities and ensure equitable outcomes for all Indian demographic groups.

Explainability

Opening the "black box." We test whether an AI's decision-making process aligns with actual clinical logic, ensuring doctors can trust and understand the output.

Uncertainty Management

Ensuring systems know when to say "I don't know." We measure a model's ability to communicate doubt and defer to a human clinician when necessary.

Our ultimate goal is to create a
National Certification Ecosystem*

We are establishing the scorecards, trust labels, and regulatory frameworks required to scale Medical AI safely across India's hospitals and public health infrastructure.

*ICMR will serve as the certification authority.

Funded By

ICMR Logo

Collaborating Institutions

IIT Delhi Logo IIT Kharagpur Logo AIIMS Delhi Logo Tata Medical Center Logo Ashoka University Logo

Get in Touch

For academic collaborations, institutional partnerships, or general inquiries regarding the TRUSTMAPS initiative.

Dr. Tanmoy Chakraborty

Associate Professor

Dept. of Electrical Engineering (Computer Technology Group)

Joint Faculty, Yardi School of Artificial Intelligence

Laboratory for Computational Social Systems (LCS2)

Indian Institute of Technology Delhi
Hauz Khas, New Delhi, Delhi 110016, India