MUMBAI, India, Jan. 23 -- Intellectual Property India has published a patent application (202641001837 A) filed by Karpagam Academy Of Higher Education; Karpagam Institute Of Technology; Renuga K; and Mohammed Safia Niyaz S, Coimbatore, Tamil Nadu, on Jan. 7, for 'ai-based medical assistant.'
Inventor(s) include Renuga K; and Mohammed Safia Niyaz S.
The application for the patent was published on Jan. 23, under issue no. 04/2026.
According to the abstract released by the Intellectual Property India: "The rapid advancement of artificial intelligence and digital health technologies has created new opportunities for improving disease detection, patient monitoring, and personalized healthcare delivery. This invention presents an AI-Based Medical Assistant designed to provide real-time health assessment, early disease risk prediction, and automated medical recommendations by leveraging advanced machine learning algorithms and multimodal data integration. The system combines electronic health records, wearable sensor data, user-reported symptoms, and physiological measurements to construct a comprehensive understanding of an individual's health status. Through deep learning architectures, the assistant identifies abnormal patterns, estimates disease probabilities, and generates predictive insights that support timely medical intervention. A natural language processing module enables intuitive human-machine communication, allowing users to interact with the system through conversational queries and receive medically relevant responses. The system incorporates a data fusion pipeline that preprocesses heterogeneous inputs using feature extraction, noise filtering, and normalization techniques to enhance diagnostic accuracy. A decision-support engine correlates patient-specific information with clinical knowledge bases to generate personalized recommendations, including lifestyle guidance, potential diagnoses, and alerts for urgent medical attention when critical deviations are detected. The AI-Based Medical Assistant operates within a cloud-enabled and scalable architecture, ensuring seamless integration with telemedicine platforms, hospital information systems, and IoT-based healthcare environments. Continuous monitoring capabilities allow proactive health management outside traditional clinical settings, reducing diagnostic delays and minimizing the workload on healthcare professionals. Additionally, the system employs robust security mechanisms, including encryption and privacy-preserving computation, to safeguard sensitive medical information. By automating preliminary diagnosis and providing continuous, context-aware medical insights, the invention significantly enhances accessibility to healthcare services, particularly in remote or resource-limited regions. The proposed system delivers a comprehensive solution that combines predictive analytics, real-time monitoring, and intelligent interaction to support preventive healthcare, improve patient outcomes, and advance next-generation medical decision-support technologies."
Disclaimer: Curated by HT Syndication.
