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, and Canada’s International Development Research Center

  • 2022
  • ongoing
  • 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