A Novel Approach to Detect Malaria using Deep Learning
Shiva Sankeerth Reddy Yarradla · International Journal for Research in Applied Science and Engineering Technology · 2020
Mosquitoes, though seeming to be tiny and fragile, transmit numerous diseases and are responsible for threatening the health of billions of people around the world. Combating these insects is becoming increasingly difficult as they are developing resistance to available insecticides. Malaria, one of the diseases transmitted through infected mosquitoes, is life-threatening in various parts of the developing world. However, early detection of this disease is propitious for proper diagnosis and effective cure. Automating the task of detecting malarial parasite from cell images using Mathematical techniques, like Machine learning algorithms or Neural Networks for deep learning, can help with the accurate diagnosis as well as funnelling resources on other important aspects of the treatment in resource-scarce areas.