AIMC Topic: Parasite Load
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Application of Machine Learning in a Rodent Malaria Model for Rapid, Accurate, and Consistent Parasite Counts.
The American journal of tropical medicine and hygiene
Sep 10, 2024
Rodent malaria models serve as important preclinical antimalarial and vaccine testing tools. Evaluating treatment outcomes in these models often requires manually counting parasite-infected red blood cells (iRBCs), a time-consuming process, which can...
Prediction of lymph node parasite load from clinical data in dogs with leishmaniasis: An application of radial basis artificial neural networks.
Veterinary parasitology
Dec 22, 2016
Quantification of Leishmania infantum load via real-time quantitative polymerase chain reaction (qPCR) in lymph node aspirates is an accurate tool for diagnostics, surveillance and therapeutics follow-up in dogs with leishmaniasis. However, qPCR requ...
Malaria Parasitemia and Parasite Density in Antiretroviral-Treated HIV-Infected Adults Following Discontinuation of Cotrimoxazole Prophylaxis.
The Journal of infectious diseases
Oct 25, 2016
BACKGROUND:  Cotrimoxazole (CTX) discontinuation increases malaria incidence in human immunodeficiency virus (HIV)-infected individuals. Rates, quantity, and timing of parasitemia rebound following CTX remain undefined.
Increasing a microscope's effective field of view via overlapped imaging and machine learning.
Optics express
Jan 17, 2022
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morpholog...
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