IIT Madras, CMC develop AI tools for early detection of kidney diseases

CHENNAI: Researchers from IIT Madras and Christian Medical College (CMC), Vellore, have developed three AI-based tools to help doctors detect kidney diseases earlier and assess their severity, potentially enabling timely intervention before significant damage occurs.

The technologies comprise a machine-learning model that predicts the risk of chronic kidney disease (CKD) using clinical and laboratory data; a deep-learning system that analyses CT scans and classifies kidneys as normal or affected by cysts, stones or tumours; and a 3D imaging platform that reconstructs kidneys from CT scans to measure tumour volume and the proportion of the kidney affected.

The CT classifier was trained on more than 12,000 images. The 3D platform, developed using open-source software, offers a low-cost and repeatable method of assessing tumour burden, providing information that could assist treatment planning.

“The team aimed to develop intelligent systems that would help clinicians make quicker and more informed decisions,” said Prof GL Samuel of IIT-Madras’ Department of Mechanical Engineering, who led the study with research scholar Jennifer Delighta, in collaboration with Prof Santosh Varughese of CMC Vellore’s Department of Nephrology.

Jennifer Delighta said early detection was of paramount importance in kidney disease and that the tools could help identify at-risk patients earlier and plan treatment more effectively.

The CKD model has been developed as a user-friendly prototype, with further work aimed at improving its accuracy and interpretability for clinicians.

Supported by IIT-Madras and the SPARC project, the study is also a step towards developing a kidney digital twin. The researchers plan to validate the models using larger patient datasets and explore their integration with wearable sensing systems for personalised kidney health monitoring.