A Comprehensive Survey of Deep Learning Techniques in Malaria Diagnosis

Malaria is a malignant disease, and it has a high mortality rate as compared to other disease. The survey of death cases in the past century reported the maximum due to malaria. Many times, it seems like a normal fever and body pain. So, many patients avoid proper medication and treatment. Many times, it is seen that the patients are unable to get cured from malaria due to inaccurate diagnosis and inproper medication. The clinical diagnosis and trials were followed in the early days, which took much time. The advancement of diagnostic techniques and processes such as rapid diagnosis technique (RDT) blood testing kit, Internet of Things (IoT) wearables with deep learning techniques, reverse transcriptase-Polymer chain reaction (RT-PCR) etc. Rapid and accurate identification of the protozoan Plasmodium parasites that cause human malaria is essential for improving the treatment and managing a lifethreatening disease. The most commonly used method for detecting Plasmodium in blood films is still microscopic analysis with Blood film staining. This article discusses the history of Plasmodium detection and evaluates the benefits and drawbacks of the current diagnostic techniques.