MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641070764 A) filed by Dr Y V Raghava Rao; Dr. M. Pallavi; D. Dennis Ebenezer; Venkata Satya Praveen Rani; Mrs. B Jaya Vijaya; M Dhivya; Dr Sathiyalatha Sarathi; Kadma Mahesh; Chigurupati Sumathi Devi; Dr. K. A. Shahul Hameed; S. Raja Shekhar; and Dr. Sundaresh. K on June 06, 2026, for Iot And Cloud-Assisted Machine Learning System For Detecting Multiple Disorders From A Single Medical Scan.
Inventors include Dr Y V Raghava Rao; Dr. M. Pallavi; D. Dennis Ebenezer; Venkata Satya Praveen Rani; Mrs. B Jaya Vijaya; M Dhivya; Dr Sathiyalatha Sarathi; Kadma Mahesh; Chigurupati Sumathi Devi; Dr. K. A. Shahul Hameed; S. Raja Shekhar; and Dr. Sundaresh. K.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: The current innovation reveals an IoT and cloud-supported machine learning method for identifying various illnesses from a single medical scan. The system incorporates IoT-enabled medical imaging devices with cloud computing infrastructure to facilitate real-time acquisition, transmission, storage, and analysis of medical imaging data. The obtained data is subjected to preprocessing procedures, such as noise reduction, normalization, segmentation, and feature extraction, to improve image quality and analytical precision. The technology utilizes sophisticated machine learning and deep learning models, such as convolutional neural networks and multi-label classification methods, to concurrently detect many anomalies and co-existing illnesses within a single scan. The produced outputs comprise diagnostic data, confidence scores, and visual annotations that emphasize areas of interest. The invention includes a decision-support module that aids healthcare practitioners in diagnostic and treatment planning, as well as a feedback mechanism for ongoing model enhancement. The cloud-based architecture guarantees scalability, remote access, and effective management of extensive datasets, hence facilitating telemedicine applications. The suggested approach markedly decreases diagnostic duration, enhances precision, and improves overall healthcare provision by facilitating intelligent, automated, and multi-disease identification from medical imaging data. FIG.1
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