rishavgiri6/covid-19-detector

My research paper on an efficient Covid-19 positive case detecting neural net based on thermal spiking and X-ray datasets to save on testing kits.

Covid-19-detector

My research paper on an efficient Covid-19 positive case detecting neural net based on thermal spiking and X-ray datasets to save on testing kits. COVID-19 tests are currently hard to come by — there are simply not enough of them and they cannot be manufactured fast enough, which is causing panic.

When there’s panic, there are nefarious people looking to take advantage of others, namely by selling fake COVID-19 test kits after finding victims on social media platforms and chat applications.

Given that there are limited COVID-19 testing kits, we need to rely on other diagnosis measures.

For the purposes of this experiment, I thought to explore X-ray images as doctors frequently use X-rays and CT scans to diagnose pneumonia, lung inflammation, abscesses, and/or enlarged lymph nodes.

Since COVID-19 attacks the epithelial cells that line our respiratory tract, we can use X-rays to analyze the health of a patient’s lungs.

And given that nearly all hospitals have X-ray imaging machines, it could be possible to use X-rays to test for COVID-19 without the dedicated test kits.

A drawback is that X-ray analysis requires a radiology expert and takes significant time — which is precious when people are sick around the world. Therefore developing an automated analysis system is required to save medical professionals valuable time.