IIT Madras and CMC Vellore researchers build AI tools for early kidney disease detection
Researchers from IIT Madras and CMC Vellore have developed AI-based tools to improve the early detection of kidney diseases. These technologies include risk prediction models, CT scan image classifiers, and 3D imaging platforms for personalized clinical assessment.
Why it matters
This innovation could significantly reduce the burden of chronic kidney disease by enabling earlier intervention and reducing the need for costly treatments like dialysis.
Researchers from the Indian Institute of Technology, Madras (IIT Madras), and Christian Medical College (CMC), Vellore, have developed a set of AI-based tools designed to assist in the early detection and assessment of kidney diseases, a press release said.
The team has developed three technologies that complement each other. The first is a machine learning model that uses clinical and laboratory information to predict the risk of chronic kidney disease (CKD). This CKD prediction model is implemented in a user-friendly prototype interface to facilitate future clinical translation.
The second is a deep learning system that automatically analyses CT scans and classifies them into four categories: normal kidney, kidney cyst, kidney stone, and kidney tumour. The image classifier has been trained with over 12,000 images and can distinguish healthy kidneys from cysts, stones, and tumours.
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