IIT Madras and CMC Vellore researchers build AI tools for early kidney disease detection
The AI tools aim to assist physicians for earlier diagnosis, which could help slow the disease process and reduce the need for expensive interventions like dialysis
Researchers from the Indian Institute of Technology Madras (IIT Madras) and Christian Medical College Vellore (CMC Vellore) have created a trio of AI tools to help detect and assess kidney diseases at an early stage, a press release announced. The team constructed three interconnected technologies that enhance each other's capabilities.
The first tool is a machine learning model that predicts the likelihood of chronic kidney disease (CKD) using clinical and laboratory data. This model is integrated into a user-friendly interface to aid in future clinical applications. The second tool is a deep learning system that scans CT images and classifies them into four categories: healthy kidneys, kidney cysts, kidney stones, and tumors.
The image classifier has been trained on more than 12,000 images and can accurately differentiate between healthy kidneys and those affected by cysts, stones, or tumors. Lastly, the third tool is a 3D imaging platform that reconstructs kidneys from CT scans, enabling precise measurement of tumor volume and the extent of kidney involvement.
This 3D imaging framework was developed using open-source software and is a step towards creating a kidney 'digital twin'. This digital twin concept involves combining AI-assisted image analysis with patient-specific 3D anatomical models to support personalized clinical decision-making. Kidney diseases often have no symptoms in their early stages and are typically diagnosed only after significant damage has occurred.
The AI tools aim to assist doctors in diagnosing the disease earlier, which could help slow its progression and reduce the need for costly interventions like dialysis. The research was spearheaded by G.L. Samuel from the mechanical engineering department at IIT Madras and Jennifer Delighta, a research scholar at IIT Madras, in collaboration with Santosh Varughese from the nephrology department at CMC Vellore.
The study received institutional backing from IIT Madras and the SPARC (Scheme for Promotion of Academic and Research Collaboration) project.
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