MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641111328 A) filed by Dr. S. P. Malarkannan; Mrs. S. Priyadharshini; Munnu Prasad V; Dr. Ravikumar H R; Gopal Jee Tiwari; and Sunita on September 16, 2026, for Ai-Based Disease Detection System Using Clinical Data Analysis.
Inventors include Dr. S. P. Malarkannan; Mrs. S. Priyadharshini; Munnu Prasad V; Dr. Ravikumar H R; Gopal Jee Tiwari; and Sunita.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: AI-Based Disease Detection System Using Clinical Data Analysis ABSTRACT The present invention discloses an AI-based disease detection system using clinical data analysis for supporting early diagnosis, risk assessment, and clinical decision-making. The system receives patient-related clinical information, including symptoms, demographic details, medical history, family history, laboratory test results, vital signs, prescriptions, lifestyle factors, and previous treatment records. The received data is processed through a preprocessing module configured to clean, normalize, validate, and structure the clinical data for accurate analysis. An artificial intelligence analysis module applies one or more machine learning algorithms to identify disease-related patterns, correlations, and abnormal clinical indicators. A disease prediction module generates outputs such as predicted disease conditions, probability scores, confidence values, risk categories, and recommendations for further medical evaluation. The system further includes a reporting module and user interface for presenting structured diagnostic support reports to healthcare professionals. In certain embodiments, the system may learn from confirmed clinical outcomes to improve prediction accuracy over time. The invention assists medical practitioners by reducing manual workload, minimizing diagnostic delays, improving early disease detection, and enhancing patient care outcomes. The system may be implemented in hospitals, clinics, diagnostic centers, telemedicine platforms, cloud servers, or healthcare information networks, while maintaining data security, privacy, and reliable clinical workflow integration capabilities.
Disclaimer: Curated by HT Syndication.
