Data

Malaria Pathogen

Central Queensland University
Anand Koirala (Aggregated by) Meena Jha (Aggregated by)
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25946/25357483.v1&rft.title=Malaria Pathogen&rft.identifier=10.25946/25357483.v1&rft.publisher=Central Queensland University&rft.description=Accurate and rapid diagnosis of malaria parasites before treatment is of utmost importance to reduce malaria mortality and morbidity. While microscopy remains the gold standard and rapid detection test (RDTs) is the present mainstay of malaria diagnosis in most large health clinics and hospitals, the quality of microscopy is frequently inadequate, and the accuracy of RDTs is reportedly falling due to specific parasite antigenic genes mutations. The detection is cumbersome in specifically remote and rural areas, which can impede the diagnosis and treatment. Delay in receiving treatment for uncomplicated malaria is often reported to increase the risk of developing severe malaria, but access to treatment remains low in most rural areas, where the burden of disease is high. The objective of this project is to develop an innovative cyber-critical technology framework for early malaria pathogen detection. The proposed translational technology solution can be useful for other diseases and regions globally.&rft.creator=Anand Koirala&rft.creator=Meena Jha&rft.date=2026&rft_rights= https://www.gnu.org/licenses/gpl-2.0.html&rft_subject=Other information and computing sciences not elsewhere classified&rft_subject=Deep Learning&rft_subject=Malaria Pathogen&rft_subject=Medical Imaging&rft_subject=Microscope Images&rft_subject=Object Detection&rft_subject=thick blood smear images&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Other view details

Full description

Accurate and rapid diagnosis of malaria parasites before treatment is of utmost importance to reduce malaria mortality and morbidity. While microscopy remains the gold standard and rapid detection test (RDTs) is the present mainstay of malaria diagnosis in most large health clinics and hospitals, the quality of microscopy is frequently inadequate, and the accuracy of RDTs is reportedly falling due to specific parasite antigenic genes mutations. The detection is cumbersome in specifically remote and rural areas, which can impede the diagnosis and treatment. Delay in receiving treatment for uncomplicated malaria is often reported to increase the risk of developing severe malaria, but access to treatment remains low in most rural areas, where the burden of disease is high. The objective of this project is to develop an innovative cyber-critical technology framework for early malaria pathogen detection. The proposed translational technology solution can be useful for other diseases and regions globally.

Data time period: 2024-01-01 to 2025-03-20

This dataset is part of a larger collection

Click to explore relationships graph
Subjects

User Contributed Tags    

Login to tag this record with meaningful keywords to make it easier to discover

Identifiers
ACN 633 798 857