Intellectual Property India Publishes Patent Application for Machine Learning-Driven Predictive Analytics For Early Detection Of Gastrointestinal Cancers

MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641076969 A) filed by Tatiparthi Sravanthi; Dr. Chintakindi Srinivas; Pujari Shivakumar; Chimmanl Supriya; Dr. Bhaskar Marapelli; and Praveen Emmadi on June 22, 2026, for Machine Learning-Driven Predictive Analytics For Early Detection Of Gastrointestinal Cancers.

Inventors include Tatiparthi Sravanthi; Dr. Chintakindi Srinivas; Pujari Shivakumar; Chimmanl Supriya; Dr. Bhaskar Marapelli; and Praveen Emmadi.

The application for the patent was published on July 03, 2026, under issue no. 27/2026.

Abstract: Abstract 5 10 15 The present invention relates to a machine learning-based predictive analytics system for early detection of gastrointestinal cancers, including cancers of the stomach, colon, rectum, esophagus, liver, and pancreas. The system aims to improve early diagnosis by analyzing complex and heterogeneous healthcare data such as electronic health records, laboratory results, imaging data, genetic information, and patient history. Conventional diagnostic methods are often invasive, costly, and result in delayed detection; therefore, an intelligent data-driven approach is required to enhance clinical decision-making. The system integrates data preprocessing, feature extraction, and advanced machine learning algorithms to identify hidden patterns associated with early-stage cancer risk. The model generates a probability score that classifies patients into low, medium, and high-risk categories, enabling timely medical intervention. The system also provides interpretable outputs to assist healthcare professionals in making accurate decisions. By enabling automated risk prediction and early warning, the invention enhances screening efficiency, reduces diagnostic delays, and supports personalized healthcare. It can be deployed in hospitals, diagnostic centers, and telemedicine platforms, offering scalable and real-time predictive support for improving patient outcomes in gastrointestinal cancer management.

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