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Jellapuram Roja
Sanga Ravikiran
Guguloth Laxman
Gajula Harshitha


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 organised and unstructured, for medical professionals and researchers. Technologies utilising 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 evaluated. 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.


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How to Cite
Roja, J. ., Ravikiran, S., Laxman, G. ., & Harshitha, G. . (2020). GRAPHICAL USER INTERFACE FOR COVID-19 DIAGNOSIS: LEVERAGING DEEP LEARNING. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 11(3), 2943–2949.
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