MUMBAI, India, Oct. 5 -- Intellectual Property India has published a patent application (202641115458 A) filed by Sri Eshwar College Of Engineering on September 26, 2026, for Federated Artificial Intelligence System For Privacy – Preserving Disease Prediction Across Distributed Healthcare Networks.
Inventors include Dr R. R. Thirrunavukkarasu; Monika Sree D; Sabarikarthika S; and Dhevavarshana D K.
The application for the patent was published on October 02, 2026, under issue no. 40/2026.
Abstract: The proposed work, Federated Artificial Intelligence System for Privacy-Preserving Disease Prediction Across Distributed Healthcare Networks, aims to develop an intelligent and secure healthcare framework for predicting diseases while protecting sensitive patient information. Conventional artificial intelligence systems often require medical data from multiple healthcare institutions to be collected in a centralized server, which may lead to privacy, security, and data-sharing concerns. To address these challenges, the proposed system utilizes Federated Learning, an approach in which machine learning models are trained locally at individual hospitals or healthcare institutions without transferring raw patient data to a central location. The locally trained model parameters are securely shared with a central aggregation server, which combines the updates to create an improved global disease prediction model. The global model can then be distributed back to participating institutions for further training and prediction. The system incorporates data preprocessing, artificial intelligence-based disease prediction, secure model aggregation, authentication, access control, and privacy-preserving mechanisms. By enabling multiple healthcare organizations to collaboratively improve disease prediction models without directly sharing confidential medical records, the proposed system enhances both prediction capabilities and patient privacy. The system can assist healthcare professionals in identifying potential disease risks and supporting early medical decision-making. Thus, the proposed Federated AI framework provides a secure, scalable, collaborative, and privacy-preserving solution for intelligent disease prediction across distributed healthcare networks.
Disclaimer: Curated by HT Syndication.
