首页|University College Dublin Reports Findings in Malaria (Efficient deep learning-b ased approach for malaria detection using red blood cell smears)
University College Dublin Reports Findings in Malaria (Efficient deep learning-b ased approach for malaria detection using red blood cell smears)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Mosquito-Borne Disease s - Malaria is the subject of a report. According to news reporting from Dublin, Ireland, by NewsRx journalists, research stated, "Malaria is an extremely malig nant disease and is caused by the bites of infected female mosquitoes. This dise ase is not only infectious among humans, but among animals as well." The news correspondents obtained a quote from the research from University Colle ge Dublin, "Malaria causes mild symptoms like fever, headache, sweating and vomi ting, and muscle discomfort; severe symptoms include coma, seizures, and kidney failure. The timely identification of malaria parasites is a challenging and cha otic endeavor for health staff. An expert technician examines the schematic bloo d smears of infected red blood cells through a microscope. The conventional meth ods for identifying malaria are not efficient. Machine learning approaches are e ffective for simple classification challenges but not for complex tasks. Further more, machine learning involves rigorous feature engineering to train the model and detect patterns in the features. On the other hand, deep learning works well with complex tasks and automatically extracts low and high-level features from the images to detect disease. In this paper, EfficientNet, a deep learning-based approach for detecting Malaria, is proposed that uses red blood cell images. Ex periments are carried out and performance comparison is made with pre-trained de ep learning models. In addition, k-fold cross-validation is also used to substan tiate the results of the proposed approach."
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