MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641077414 A) filed by Keshav Memorial Institute Of Technology on June 23, 2026, for Medipredict Hub: A Centralhub For Multiple Health Predictions.
Inventors include Ms. Dr. S Archana; Mr. K Rajesh Kumar; Mr. Marimganti Kiran Kumar; Ms. Anusha Velishetty; Mr. Chiluveru Nagadhanush; Mr. Srigowrav Chandra; Mr. Nareen Sai Baddul; Mr. Garlapati Manoj Kummar; and Mr. Ganipshety Mokshith.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: Medi Predict Hub is a comprehensive web-based healthcare analytics platform that consolidates multiple machine learning-driven prediction models into a single, user-friendly interface. Built using Python frameworks like Flask/Django with integrated frontend technologies, the system democratizes access to predictive health modeling for both healthcare professionals and individuals seeking preventive care insights. The platform leverages Python's scientific computing ecosystem, including scikit-learn, TensorFlow, and pandas, to implement sophisticated prediction algorithms across various health conditions. It features specialized modules for cardiovascular disease risk assessment, breast cancer probability estimation, diabetes onset prediction, and other critical health screenings. Each module employs carefully trained machine learning models using validated medical datasets and clinical parameters. Medi Predict Hub offers real-time risk assessment, personalized health recommendations, and comprehensive reporting capabilities while maintaining strict data security and healthcare compliance standards. The platform's modular Python-based architecture ensures scalability, maintainability, and easy integration of additional prediction models, bridging the gap between complex analytics and practical healthcare applications through evidence-based predictive modelling. Medi Predict Hub represents a significant advancement in accessible healthcare analytics, transforming complex machine learning algorithms into practical clinical tools. By consolidating multiple prediction models within a unified Python-based platform, it empowers both healthcare professionals and individuals with data-driven insights for proactive health management. This innovative approach to predictive healthcare modeling demonstrates the potential for technology to enhance early detection and intervention strategies, ultimately contributing to improved patient outcomes and reduced healthcare costs.
Disclaimer: Curated by HT Syndication.
