Our lab has secured $20,000 from Google.org and $15,000 in support from OpenAI to accelerate our work
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Benchmarking clinical decision-support AI models en route to developing India's first medical foundation model - trained for Indian clinical contexts and languages.
Leads: Prof. Anurag Agrawal (KCDH-A, Ashoka); Dr. Mona Duggal (ICMR); Dr. Annie Hartley (EPFL/Harvard). CRASH Lab lead: Dr. Suvrankar Datta; Dr. Sarah Khan; Dr. Mayank Garg; Swarna Radhakrishnan; Siddharth Valecha.
Status: Active - Gates Foundation.
Creating scalable autonomous pipelines to learn how individual radiologists write their reports, so that AI-generated radiology reports preserve each doctor's reporting voice while staying medically accurate.
Active - Self-Funded
View research →RadLE - Can Today's Leading AI Models Read Medical Scans Like a Radiologist?
An ongoing study comparing how the newest reasoning AI models interpret radiology scans against practicing radiologists - and how confident the AI is in its own readings.
Active - Simons Foundation
Creating the first standardised classification of the visual reasoning mistakes AI models make on radiology images - so they can be spotted, measured, and fixed.
Active - Simons Foundation
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