Only a few spare seats remain in the crowded waiting room at Kiruddu General Hospital, overlooking Lake Victoria on Kampala’s southern tip. Doctors in white coats walk quickly past tired patients clothed in bright, patterned kitenge fabrics.
Upstairs, lab technicians tackle a mounting pile of slides for microscopic examination – staring through the eyepiece at blood samples suspected of containing malaria parasites or the bacteria that causes tuberculosis. It’s a time-consuming process, with each slide finely adjusted by hand around 100 times before a confident diagnosis can be given.
But this is changing. Uganda’s first Artificial Intelligence (AI) lab, at Makerere University, has developed a way to diagnose the blood samples using a cell phone.
The program learns to create its own criteria based on a set of images that have been presented to it previously. It learns to recognize the common features of the infections.
“Microscopists usually have a problem with their eyes because of overstraining,” says Martha Nakaya – an experienced lab technologist of 11 years.
Lab technicians should process no more than 25 slides each day, but a lack of qualified workers lead some to process four times as many.
“We have so many patients who may require malaria and TB tests, and we have one technician looking at all these slides,” agrees doctor Alfred Andama, standing in the busy lab. “Apart from affecting their eyes, this also compromises their ability to report correctly what they see.”
Andama is among a team of healthcare workers and coders trialling the prototype device that could put an end to this painstaking process – diagnosing patients more quickly, cheaply and accurately.
So how does it work?
Clamped in place over one microscope eyepiece, a basic smartphone brings to light a detailed image of the blood sample below – each malaria parasite circled in red by artificially intelligent software.
Nakaya verifies that the computer is correct, pointing to the tell-tale dot and comma shape of the malaria parasite.
PhD researcher, Rose Nakasi, 31, is the lead scientist behind this technology. “Almost everyone in Uganda, including me, has had malaria” says Nakasi, who is a researcher in computer science. “It affects me as a person, and it affects Uganda. So I feel attached and want to contribute in any way that I can to its proper diagnosis.”