Open AccessDetection of Malaria Using Machine Learning
Author(s) -
S. T. Sawale,
Apeksha P. Mahajan,
Shital B. Borle
Publication year - 2021
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-1609
Subject(s) - malaria , blood smear , plasmodium (life cycle) , diagnosis of malaria , plasmodium falciparum , medicine , computer science , virology , immunology , artificial intelligence , parasite hosting , world wide web
“Malaria is a blood-borne disease caused by Plasmodium-borne diseases. Common methods of detecting malaria include preparing a blood smear and examining the contaminated blood smear using a microscope to detect Plasmodium virus infection, which relies heavily on the techniques studied. At the bottom of this paper, with the aim of discriminating against malaria parasites, shallow study tools are used against traditional methods, which have other pitfalls related to understanding and disunity. The described method determines the spread of malaria with the help of photographs taken of patients without blood transfusions or the need for specialists.