Abstract
MACHINE LEARNING APPROACH FOR CLASSIFICATION OF MALARIA DISEASE

Sanjay Nag, Nabanita Basu and Prof. Samir Kumar Bandyopadhyay*

ABSTRACT

Malaria disease, a parasitic disease health problem, occurs due to damaging of red blood cells in the blood. It is difficult to identify in a clinical set-up. Various methods have been found to predict or diagnosing the malaria disease. Malaria Diagnosis is normally done by visual microscopy. It is time consuming and offers low accuracy due to operator's tiredness. So it is required to design a system which is able to take photos of blood smears using motorized sophisticated microscope. The image processing task is launched after gathering enough samples for microscopy. The outcome is then placed before the doctor for the final decision. It is observed that machine learning techniques have wider applicability for critical diagnosis of malaria which in turn helps the clinicians for diagnosing the disease. This paper utilizes the machine learning approach for classification malaria disease.

Keywords: Anopheles Mosquito, Parasites. Nucleus and Cytoplasm.


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