Rapid diagnosing is crucial for controlling malaria. Various studies have aimed at developing machine learning models to diagnose malaria using blood smear images; however, this approach has many limitations. This study developed a machine learning model for malaria diagnosis using patient information.
The microscopic examination of Giemsa-stained thin and/or thick blood films (Giemsa microscopy) is the standard method of malaria diagnosis. However, the results of the diagnosis significantly depend on the skills of clinical technicians. Furthermore, sample preparation and analysis are laborious and time-consuming. Therefore, in this study, we investigated if a commercially available fluorescent cell counter, LUNA-FL, was useful for the detection of Plasmodium parasite and the estimation of parasitemia.
Malaria continues to be a major global health problem, with over 228 million cases and 405,000 deaths estimated to occur annually. Rapid and accurate diagnosis of malaria is essential to decrease the burden and impact of this disease, particularly in children. We aimed to review the main available techniques for the diagnosis of clinical malaria in endemic settings and explore possible future options to improve its rapid recognition.
Malaria has been for millennia one of the best known and most destructive diseases affecting humans. Its high impact has aroused great interest for the development of new effective and reliable diagnostic techniques. Recently it has been recently published that hairs from mammal hosts are able to capture, hold and finally remove foreign DNA sequences of Leishmania parasites.
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 and to control a devastating disease that affects millions of people living in endemic areas. The microscopic examination of Giemsa‐stained blood films still remains the gold‐standard in Plasmodium detection today.
Historically, the global community has focused on the control of symptomatic malaria. However, interest in asymptomatic malaria has been growing, particularly in the context of malaria elimination.
While the malaria death count in Cambodia dropped to just one case in 2016, a new threat to the race against the disease arises in south-eastern Asia: superbugs. A superbug is a drug-resistant, human-killing parasite that modern medicine struggles to combat.
If you care for patients with cerebral malaria or know someone who does, then we would appreciate your help in distributing this short survey.
Please use the following link to complete the survey: Cerebral Malaria Diagnosis Survey
I am an ophthalmologist with a background in malaria biology, and I am leading a survey study to understand how clinicians diagnose cerebral malaria.