MUMBAI, India, July 30 -- Intellectual Property India has published a patent application (202641088001 A) filed by Dvr & Dr. Hs Mic College Of Technology; Dr. Rrajaramesh Merugu; Dr. M. Narendra; Mr. Kanchi Manipal; and Mr. Boyalapalli Anil Kumar on July 18, 2026, for System And Method For Artificial Intelligence-Based Early Detection, Risk Prediction, And Clinical Decision Support For Hepatitis Disease.
Inventors include Dr. Rrajaramesh Merugu; Dr. M. Narendra; Mr. Kanchi Manipal; and Mr. Boyalapalli Anil Kumar.
The application for the patent was published on July 24, 2026, under issue no. 30/2026.
Abstract: The invention reveals a system and method which uses Artificial Intelligence (AI) and machine learning to achieve early detection and diagnosis of hepatitis. Hepatitis is a severe liver disease that in most cases, does not display noticeable symptoms at an early stage, so that timely diagnosis is delayed and it increases the risk of major liver damage. Current diagnostic practices usually take many laboratory tests, physical exams, and expert opinion, so they are not only time-consuming and costly; they are also less available in under resourced environments. To overcome such issues here an author develops an intelligent clinical decision support system capable of accurate prediction of hepatitis based on clinical and laboratory patient data. The method proposed makes use of three machine learning techniques that are Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Artificial Neural Network (ANN) to classifying patient data into different diagnostic labels. This machine learning setup includes various processes such as data cleaning, feature extraction, data normalization, model learning, and predictive analysis. Comparative studies between the machine learning techniques help in deciding the best predictive model or the possibility of developing an enhanced version of an integrated hybrid approach of these models. The created system performs hepatitis risk assessment very fast and with no need for human intervention This way, it not only supports health professionals to take the right decisions based on the clinical circumstances but also permits initial screening at home. The new creation can be made a part of hospital information systems, electronic health record systems, cloud-based medical platforms, and remote medicine services for better reach and capability. Through providing hepatitis diagnosis at an early stage, reducing the diagnostic complexity, and allowing clinicians to intervene in timely manner the invention leads to better patient health, more efficient use of medical resources, and further development of AI-supported healthcare systems in the intelligent mode.
Disclaimer: Curated by HT Syndication.
