Skip to content
Live newsroom 124 readers online
Thursday, September 3, 2026 Live Sync: Just now
BreakingCrocodile Hunter left best mate with scars but not a single regret
Important SWING VWAGY Stage 1 (Conv: 2/5 | Size: 10%)

IIT Madras and CMC Vellore researchers build AI tools for early kidney disease detection

Account subscription benefits alongside Premium Stories, Editorials, Opinions and more. Unlock these with Subscription The View From India Looking at World Affairs from the Indian perspective. First Day First Show News and reviews from the world of cinema and streaming. Today's Cache Your download of the top 5 technology stories of the day. Science For […]

By deepak · September 3, 2026 · 2 min read

Account subscription benefits alongside Premium Stories, Editorials,
Opinions and more. Unlock these with Subscription

The View From India
Looking at World Affairs from the Indian perspective.

First Day First Show
News and reviews from the world of cinema and streaming.

Today's Cache
Your download of the top 5 technology stories of the day.

Science For All
The weekly newsletter from science writers takes the jargon out of science and puts the fun in!

Data Point
Decoding the headlines with facts, figures, and numbers

THEdge
At the cutting edge of education and careers

Health Matters
Ramya Kannan writes to you on getting to good health, and staying there

Gender Agenda
Stories from beyond the binary.

The Hindu On Books
Books of the week, reviews, excerpts, new titles and features.

Published – September 03, 2026 03:27 pm IST – CHENNAI

Image used for representation
| Photo Credit: Getty Images

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.

Source: Read the original article on www.thehindu.com

Important Legal & Financial Disclaimer

FutureKnowledge is an automated financial intelligence aggregator. The information provided on this website does not constitute investment advice, financial advice, trading advice, or any other sort of advice and you should not treat any of the website's content as such. We are not registered with the SEC, SEBI, or any regulatory agency. Automated AI-generated content may contain errors. Always conduct your own due diligence and consult your financial advisor before making any investment decisions.

© 2026 FutureKnowledge Intelligence. All rights reserved.