MUMBAI, India, Feb. 6 -- Intellectual Property India has published a patent application (202521113232 A) filed by LNCT University, Bhopal, Madhya Pradesh, on Nov. 18, 2025, for 'a hybrid algorithms integrated with pca for prediction of epileptic diseases on machine learning.'
Inventor(s) include Priyanka Singh; and Dr. Divyarth Rai.
The application for the patent was published on Feb. 6, under issue no. 06/2026.
According to the abstract released by the Intellectual Property India: "A Hybrid Algorithms Integrated with PCA For Prediction of Epileptic Diseases on Machine Learning Epilepsy is a neurological disorder characterized by sudden and recurrent seizures, often caused by abnormal electrical activity in the brain. Accurate and timely prediction of epileptic seizures is vital for effective patient care and clinical decision-making. This research proposes a Hybrid Machine Learning Model integrated with Principal Component Analysis (PCA) for efficient and precise prediction of epileptic diseases. PCA is employed to reduce data dimensionality and eliminate redundant features from EEG signal datasets, thereby enhancing model performance and computational efficiency. The hybrid framework combines multiple classifiers-such as Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN)-to leverage their complementary strengths in classification and pattern recognition. Experimental evaluation demonstrates that the proposed PCA-based hybrid model achieves higher accuracy, sensitivity, and specificity compared to traditional single-algorithm approaches. The results confirm that integrating PCA with a hybrid ensemble of classifiers significantly improves epileptic seizure prediction while minimizing processing time and data complexity. This study highlights the potential of hybrid machine learning models as reliable tools for automated diagnosis and early detection of epileptic disorders, contributing to the advancement of intelligent healthcare systems."
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