MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641059558 A) filed by Vishnu Engineering College For Womena on May 09, 2026, for A Deep Learning Enabled Web-Based Malaria Diagnosis System Using Yolov8 Object Detection.
Inventors include Ms. Y. Gayatri; Mr. N. Praveen Kumar; M. Sri Kavya; V. Meenakshi; Y. Syasyanka Ratna Priya; and Y. Harshitha.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: Malaria is a serious infectious disease caused by Plasmodium parasites. Affecting millions of people around the world. The timely and accurate diagnosis is essential for treatment. Malaria diagnosis through microscopic evaluation of blood smear is time consuming and needs expertise of lab experts. Delay and human error may take place. The proposed system is found to be effective at detecting malaria. a deep learning model utilizing VISAL and few-shot learning techniques. The system identifies and classifies blood cells from microscopic images by detecting different cells including healthy cells and malaria parasite such as ring, trophozoite, schizont, and gametocyte. VISAL enhances the model’s attention to critical parasite areas while few-shot learning allows the model to perform adequately with minimal labeled data. The developed model is incorporated into the backend server and mobile application. which provides real-time diagnostic results from the uploaded blood smear images by users. The system proposed offers accurate and fast detection of malaria that can be used in the hospital environment especially in rural and resource-limited areas.
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