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<!DOCTYPE HTML>
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<h2>CoronaX</h2>
<p>A Deep Convolutional Neural Network Model for Reliable Detection of
SARS- Related coronavirus (COVID-19)</p>
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<a href="#" class="image fit"><img src="images/covid19.gif" alt="" /></a>
<h3>ABSTRACT</h3>
<p>A new virus affecting the respiratory system of humans and animals called
the novel coronavirus made the headlines for triggering an outbreak of the breathing
illness worldwide in 2019. It spread throughout the world in a very short span of time,
affecting people on a large scale and causing thousands of deaths which is a major challenge
for healthcare professionals. Government is completely locking their territories down for
preventing the spread of this disease. In the present scenario, we would like to contribute
by proposing a novel method of designing a real time system for efficiently diagnosing COVID-19
to keep a precise record of positive cases so that people who are diagnosed positive can be treated
on time and can be prevented from being a carrier of the virus being transmitted to more people with
a testing accuracy of 94%.
</p>
<h3>OBJECTIVES</h3>
<p>The principal objective of the invention is to provide a software model for efficient
and reliable detection of presence of COVID-19 in order to the determine its presence
in suspected patients under proper supervision of medical health care professionals.</p>
<ul>
<li> It is beneficial in timely diagnosis of COVID-19 patients for preventing its spread as it
has become a pandemic and is spreading at a very rapid rate.</li>
<li> It can help in providing accurate number of patients diagnosed with COVID-19 which
can be used in medical research.</li>
<li> Identifying COVID-19 in early stages of diagnosis can reduce the death rate.</li>
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<ul>
<p>Provisional Patent filed on April 6, 2020<br />
Patent Office: India <br />
Patent application number: 202011015157<br />
Co-inventors: Mr. Shubham Vashisth & Dr. S. Saraswat<br /> </p>
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