Our lab has secured $20,000 from Google.org and $15,000 in support from OpenAI to accelerate our work
Read MoreResearch Project
Using deep learning on standard chest radiographs as a low-cost, non-invasive way to flag patients at risk of coronary artery disease - built for screening in India's resource-constrained healthcare settings.
Leads: Dr. Deepak Mishra (IIT Jodhpur), Dr. Anurag Agrawal & Dr. Suvrankar Datta (Ashoka), Dr. Santosh Satheesh (JIPMER); Dr. Ganesh (KMC Manipal). CRASH Lab lead: Dr. Suvrankar Datta; Gadha Lakshmi.
Status: Active - ANRF Advanced Research Grant.
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
View research →Western-trained radiology AI often underperforms on Asian patients. We are building and validating vision-language models for chest imaging designed specifically for Indian and Singaporean populations.
Active - DST - A*STAR
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