Revolutionizing Malaria Diagnosis: A Deep Learning Approach
Ashok Reddy Kandula, Kalyanapu Srinivas, Likitha Sai Gottipati, Harika Kamma, Mohitha Munagala, Priyadarshini Ramachandran · 2023
Malaria is a hazardous disease affecting millions worldwide, and early, accurate diagnosis is crucial for leveraging effective treatment. The proposed method involves training the VGG19 algorithm on a large dataset of images that detects the presence of malaria parasites. The outcomes show the effectiveness of the suggested strategy, with a 95 percent accuracy rate in identifying cells infected with malaria. The suggested method can potentially increase the effectiveness of malaria diagnosis, especially in an environment with limited resources and access to qualified medical personnel.