We've built a low-cost lens attachment to the smartphone camera that images blood at high magnification. The attachment magnifies/focuses on the sample by means of a 1mm ball lens. Most importantly, we've implemented computer vision to algorithmically count and identify cells in the bloodstream to automatically diagnose disease/conditions.

For more than 2 centuries, cell morphology - or the practice of viewing/analyzing a person's blood in order to diagnose conditions - has been the primary way to approach medicine.

Literally every facet of the medical world relies on blood cell analysis to diagnose conditions. Malaria, Chronic Diseases, Cancers, and all sorts of Parasites are all first detected when a physician manually recognizes the given cell type in your blood sample.

Yet, despite the critical nature of blood analysis to the medical industry - the process has hardly changed from its long, expensive form for 150 years: go to the doctor, get a large sample taken, wait for a couple days for a trained professional to analyze the blood, and then receive your report. Athelas changes all that.

In short - a malaria test that requires no expertise, takes a few seconds, and costs next to nothing. All on a smartphone - holding potential to save thousands of lives.

Furthermore, through predictive cell counting, Athelas can mimic the process conducted in lab-grade environments in rural areas.

The product can benefit those in rural and suburban areas alike by providing faster and cheaper alternatives to existing diagnostic procedures. In rural areas, the tech will really shine - providing previously unavailable diagnostic skills through the power of artificial intelligence and computer vision.

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