MUMBAI, India, July 11 -- Intellectual Property India has published a patent application (202541060947 A) filed by MLR Institute of Technology, Hyderabad, India, on June 26, for 'hybrid approach for prediction of heart disease using informative entropy-based random forest.'

Inventor(s) include Mrs. J. Adilakshmi; Mrs. S. Viharika; Mr. B. Veerasekharreddy; and Dr. Venkata Nagaraju Thatha.

The application for the patent was published on July 11, under issue no. 28/2025.

According to the abstract released by the Intellectual Property India: "Cardiovascular diseases (CVDs), which affect the heart and blood vessels, are now the leading cause of death globally, including in India. The bulk of the world's mortality in the previous several decades has been attributable to cardiovascular illnesses. Consequently, a trustworthy, precise, and workable method is required for the early detection of these illnesses so that the right treatment can be given. A number of medical datasets have been automated through the application of machine learning algorithms and methodologies to explore massive and complex data sets. Utilising the patient's medical history in our model, we devised a method to ascertain the likelihood of a cardiac diagnosis. It proposes to detect this disease by considering the dataset obtained from the Cleveland repository and utilizing the Genetic Algorithm for feature extraction, and performing the feature level fusion because of its automatic and efficient learning. Moreover, Fast Track Gram Matrix-principal Component Analysis (FTGM-PCA) is implemented for reducing the dimensionality and fusion to resolve the issues related to over fitting, reducing space and time complexity and eliminating the irrelevant data for improving the performance of the classifier. Moreover, the effective classification is performed via a newly implemented technique called Informative Entropy-Based Random Forest (IEB-RF) because of its capability to achieve a huge accuracy rate and also manage the flexibility of huge data."

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