Diagnosing Malaria with a Mobile Device
A high-school student hopes to change the face of third-world illness with his proposed phone add-ons
Cooked up over a weekend in a room thronged with programmers, a blood-testing kit for smartphones won the first ever YC Hacks competition in Mountain View, CA this month. With a simple, improvised demonstration involving an iPhone and a toilet paper roll, the project entitled Athelas swayed judges and onlookers alike by presenting a cheap, pocket-sized method for detecting malaria and other maladies.
In brief, Athelas' contest application proposes using lens attachments with camera phones to magnify and document blood samples and an app to analyze the images. Tanay Tandom, the project's creator and a high-school senior in Cupertino, CA, explains that, significantly, his product “implement[s] computer vision to algorithmically count and identify cells in the bloodstream to automatically diagnose disease/conditions.” The lens attachment, a 1mm ball lens with an estimated production cost of $5, currently supplies images which allow for an accuracy rate of 70-75% with “live blood samples.” When supplied with training data, the diagnosis program is reported as having an accuracy rate of of 90-95% with cell identification.