Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 11, Issue 3


Published
on


Pages

2943-2949


DOI

Article

GRAPHICAL USER INTERFACE FOR COVID-19 DIAGNOSIS: LEVERAGING DEEP LEARNING


Authors

Roja Jellapuram Affiliation:
Assistant Professor, Department of CSE Engineering Abdul Kalam Institute of Technological Sciences, Kothagudem, Telangana
, Ravikiran Sanga Affiliation:
Assistant Professor, Department of CSE Engineering Abdul Kalam Institute of Technological Sciences, Kothagudem, Telangana
, Laxman Guguloth Affiliation:
Assistant Professor, Department of CSE Engineering Abdul Kalam Institute of Technological Sciences, Kothagudem, Telangana
and Harshitha Gajula Affiliation:
Student, Department of CSE Engineering Abdul Kalam Institute of Technological Sciences, Kothagudem, Telangana


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 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.


Keywords


Citation

Jellapuram, R., Sanga, R., Guguloth, L., & Gajula, H. (2020). GRAPHICAL USER INTERFACE FOR COVID-19 DIAGNOSIS: LEVERAGING DEEP LEARNING. Turkish Journal of Computer and Mathematics Education, 11(3), 2943–2949.

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