Datasets for AI Based Diagnosis of Malaria
Rose Nakasi, (PI), Darlington Akogo (Co-PI), Joyce Nakatumba-Nabende, Chodrine Mutebi, Jeremy Tusubira, Alvin Nahabwe
Funder: Lacuna Fund – A Collaborative Fund between the Rockefeller Foundation, Google.org and Canada’s International Development Research Center
- 5 min read
The project will provide accessible, large and quality geo-tagged datasets of microscopy thick and thin blood smear images from Uganda and Ghana for improved field-based diagnosis of malaria.
This larger and more representative dataset will
(1) provide a standardized dataset for reliable field-based image analysis,
(2) support the development of improved and more robust models for malaria diagnosis.
(3) and the geolocation information will inform real-time disease risk mapping for improved stake-holder interventions for malaria