AiAi.care volunteer project is working to reduce Tuberculosis 👾 and Lung Cancer screening time and screening costs by teaching computers to "see" and interpret chest X-rays how a human Radiologist would.
We are using 700,000 labeled chest X-Rays dataset + Deep Learning to build an FDA 💊 approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi.care CAD will be distributed for free to emerging nations and charitable hospitals everywhere 🌏
Why Tuberculosis Algorithm
One in four people are exposed to M. Tuberculosis bacterium, but it does not become active TB unless mixed with malnutrition and overcrowding. These two factors have earned TB the nickname "disease of poverty".
Emerging nations have 12x fewer Radiologists compared to developed world, so TB patients often remain undetected while continuing to spread the bacterium further through air (coughing, sneezing, spitting). In recent years Tuberculosis is massively resurgent with 8.6 million new cases of active TB diagnosed worldwide in 2012. India accounted for a record 2.76 million new cases in 2016. A lot of these cases are MDR (Multi-Drug Resistant) TB strain.
AiAi's free TB screening tool will help emerging nations overcome shortage of Radiologists by screening X-rays within 45 seconds of capture. Early results show that our algo can potentially deliver expert-panel grade TB screening capabilities to underserved regions.