Evaluation of the Parasight Platform for Malaria Diagnosis
Taken together, these findings indicate that the Parasight platform demonstrates improved accuracy, compared with our previous prototype devices, and provides significant value for the malaria diagnostic community. The distribution of the device at strategic locations will lead to improved disease treatment and screening, ultimately resulting in an expedited roadmap to eradication.
Computer Vision Malaria Diagnostic Systems — Progress and Prospects.
In this review, we discuss the most advanced computer vision malaria diagnostic technologies and investigate several of their features which are central to field use. Additionally, we discuss the technological and policy barriers to implementing these technologies in low-resource settings world-wide.
An Enhanced Computer Vision Platform for Clinical Diagnosis of Malaria.
Accurate malaria diagnosis is necessary to prevent unnecessary deaths and curb malaria drug resistance related to unnecessary treatment. While numerous diagnostic assays exist, the need for a low-cost, rapid and highly accurate malaria test remains. Here we evaluate the diagnostic performance of a computer vision platform, the Sight Diagnostic P2 device for malaria diagnosis, speciation and parasite quantification.
Computer-vision-based technology for fast, accurate and cost effective diagnosis of malaria.
Microscopy has long been considered to be the gold standard for diagnosis of malaria despite the introduction of newer assays. However, it has many challenges like requirement of trained microscopists and logistic issues. A vision based device that can diagnose malaria, provide speciation and estimate parasitaemia was evaluated.
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