Concurrent advances in information technology infrastructure and mobile computing power
in many low and middle-income countries (LMICs) have raised hopes that artificial …

The African continent carries the greatest malaria burden in the world. Falciparum malaria
especially has long been the leading cause of death in Africa. Climate, economic factors …

Objective: This work investigates the possibility of automated malaria parasite detection in
thick blood smears with smartphones. Methods: We have developed the first deep learning …

Background Rapid diagnosing is crucial for controlling malaria. Various studies have aimed
at develo** machine learning models to diagnose malaria using blood smear images; …

Background Microbiologists are valued for their time-honed skills in image analysis,
including identification of pathogens and inflammatory context in Gram stains, ova and …

Background Manual microscopic examination of Leishman/Giemsa stained thin and thick
blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this …

Abstract Background Microscopic examination of Giemsa-stained blood films remains the
reference standard for malaria parasite detection and quantification, but is undermined by …

Malaria remains a global health problem, with 247 million cases and 619,000 deaths in
2021. Diagnosis of Plasmodium species is important for administering the appropriate …

Fast and effective detection of the causative agent of malaria in humans, protozoan
Plasmodium parasites, is of crucial importance for increasing the effectiveness of treatment …

Background Manual microscopy remains a widely-used tool for malaria diagnosis and
clinical studies, but it has inconsistent quality in the field due to variability in training and field …