MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641096133 A) filed by Velammal Institute Of Technology; Dr. S. Soundararajan; Ms. Ponsangeetha A; Ms. Krishnavaratha K; Mr. R. Venkadesh; R. Vishwashree; and J. Yasmin on August 08, 2026, for Ai Driven Visual Question Answering In Healthcare.
Inventors include Dr. S. Soundararajan; Ms. Ponsangeetha A; Ms. Krishnavaratha K; Mr. R. Venkadesh; R. Vishwashree; and J. Yasmin.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: The present invention introduces an AI-powered web application for the early prediction and monitoring of diabetes and associated chronic diseases by integrating Machine Learning and Deep Learning techniques. The system enables intelligent analysis of patient health data, where clinical parameters such as age, blood pressure, glucose level, cholesterol, and body mass index are collected, preprocessed, and analyzed using predictive algorithms. In addition, scanned medical reports and diagnostic data are processed using Convolutional Neural Networks (CNN) to extract meaningful features and enhance prediction accuracy. The system generates real- time risk assessments and provides early warning alerts to support timely medical intervention and preventive healthcare.The framework also incorporates a user- friendly web interface that allows seamless data input, report uploading, and instant result visualization. It ensures secure data handling through authentication and protected storage mechanisms while maintaining patient privacy. The application supports continuous health monitoring by tracking user data over time and identifying patterns indicating potential health deterioration. Designed to be scalable and accessible, the system improves healthcare delivery, especially in remote areas, by providing reliable and automated decision-support tools. By combining intelligent analytics, real-time processing, and secure data management, the invention establishes an efficient and future-ready solution for enhancing early diagnosis and improving overall patient outcomes.
Disclaimer: Curated by HT Syndication.
