Volume 19 No 1 (2021)
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UTILIZING DEEP LEARNING TO DIAGNOSE COVID-19 THROUGH A GRAPHICAL USER INTERFACE
LAKKIREDDY PRIYANKA, VARUN MARAMRAJ
Abstract
Tens of thousands of people have died as a result of the COVID-19 epidemic, which has shut down transport and plunged the world into an unprecedented state of turmoil. COVID-19 still presents a significant risk to public health. This article claims that AI can be used to combat the virus. Generative Adversarial Networks (GANs) have been demonstrated to be effective for this goal (GAN). Using an integrated bioinformatics approach, these systems facilitate the easy access to data from a variety of sources, both organized and unstructured, for medical professionals and researchers. Technologies utilizing artificial intelligence (AI) can expedite COVID-19 diagnosis and treatment. In order to choose inputs and targets for an Artificial Neural Network-based tool for COVID-19 challenges, a large number of medical reports were analyzed. Furthermore, a variety of data types, including clinical data and medical imaging, are inputs into this platform that can improve the performance of the introduced technique and lead to optimal outcomes in real-world applications.
Keywords
Tens of thousands of people have died as a result of the COVID-19 epidemic, which has shut down transport and plunged the world into an unprecedented state of turmoil.
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