Researchers from the Indian Institute of Technology Madras (IIT Madras) and Christian Medical College (CMC), Vellore, have developed a suite of Artificial Intelligence (AI)-based tools designed for the early detection, classification, and precise assessment of kidney diseases, which affect millions worldwide.

The collaborative research team created three complementary technologies: a machine learning model that utilizes clinical and laboratory data to predict chronic kidney disease (CKD) risk, a deep learning system trained on over 12,000 images to automatically categorize CT scans into normal kidneys, cysts, stones, or tumors, and an open-source 3D anatomical imaging platform that reconstructs kidneys from CT scans to accurately calculate tumor volume and disease involvement.

Led by Prof. G.L. Samuel and Ms. Jennifer Delighta from IIT Madras, alongside Prof. Santosh Varughese from CMC Vellore, the project provides clinicians with rapid, standardized diagnostic support to enable earlier intervention and reduce reliance on expensive therapies like dialysis. Supported by IIT Madras and the SPARC initiative, this research represents a critical step toward developing a "Digital Twin" platform for personalized clinical decision-making. Moving forward, the joint team plans to expand clinical validation across multi-center datasets and integrate these AI technologies with wearable sensing platforms for long-term health monitoring.

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