The AI project, founded by Julian Jewel Jeyaraj which has been globally appreciated for its recent air quality app, has brought another app that uses NIH data sources and applies machine learning on it for predictive analytics; to detect COVID-19 with 99% accuracy.
NEW DELHI--(BUSINESS WIRE)--Julian Jewel Jeyaraj has announced the launch of JJAIBOT (Julian Jewel’s Artificial Intelligence Bot), an online app that will help doctors and can diagnose Covid-19 using CT scans with good accuracy. The official launch of the app happened soon after the Pandemic got worse and the app can be used from anywhere in the world.
The AI initiative was built by Jeyaraj to create technology awareness towards environment protection, wildlife conservation and mental illness. JJAIBOT initiative develops computer software that helps with urgent issues that have a huge impact on society and the ecosystem.
Julian Jewel Jeyaraj believes that JJAIBOT will provide a very efficient, fast and accurate way to diagnose Covid-19. Also, the use of JJAIBOT will have an impact on reducing the cost of managing pandemics. JJAIBOT is a modern solution to this global pandemic. With the economic downturn, the diagnosis of Covid-19 has become even more difficult and less affordable. JJAIBOT is a solution that could be used and facilitate the work of doctors.
JJAIBOT consists of using two parameters to diagnose Covid-19:
- X-ray PA view of the chest
- CT scan of the lungs.
The X-ray PA view of the chest is a method through which we can have an image of the chest using X-rays. This method is quite effective, and we can have a clear vision of the organs and their condition.
While through the CT scan, we get an image of the lungs and their state of health. It is worth noting that the CT scan is very accurate. The sensitivity of the CT scan is 98%, much higher compared to RT-PCR testing sensitivity of 71%.
Early and rapid diagnosis of Covid-19 can save lives, and here JJAIBOT has made a revolution in medicine.
More details about the app can be found at: https://www.jjaibot.org/home/casestudies/