An innovative deep learning approach for COVID-19 detection with X-ray images and infected user tracking through blockchain
by K. Vimal Kumar; Shriram K. Vasudevan; Nitin Vamsi Dantu
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 14, No. 2, 2022

Abstract: The COVID-19 pandemic has shocked the globe with an enormous number of people infected and a large death toll across several nations. A deadly virus has many victims but no country could stand out when it comes to producing a vaccine. The virus is so dangerous that it spreads rapidly through human contact and a person who is infected will infect around 600 people a month. It is so fast that more than 50,000 people are affected in one day in some countries and more than 1,000 people die in one day. There are many patients but not enough doctors and hospitals to treat them as the infection grows exponentially. No doctor can examine chest X-ray in thousands and have fast turnaround. We want to create a solution to reduce the workload on doctors, to easily determine whether a chest X-ray pneumonia is due to coronavirus or not, so that the rapid spread can be controlled and proper cure could be given to patients. Here we also add the distributed ledger technology called blockchain, which helps in monitoring the patient health data and thus it helps in having the complete history of the patient.

Online publication date: Mon, 28-Feb-2022

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