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.
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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.
And the third is a 3D imaging platform that recreates kidneys from CT scans to precisely assess tumour volume and the percentage of kidney involvement.
The 3D imaging framework was developed using open-source software and is a step toward the development of a kidney ‘digital twin’, integrating AI-assisted image analysis with patient-specific 3D anatomical models for personalised clinical decision-making.
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The research was led by G.L.
Samuel, department of mechanical engineering, IIT Madras, and Jennifer Delighta, research scholar, IIT Madras, in collaboration with Santosh Varughese from the department of nephrology, CMC Vellore.
The research received institutional support from IIT Madras and the SPARC (Scheme for Promotion of Academic and Research Collaboration) project, the press release said.
