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NDCOV-19 2020 : NEURAL NETWORKS AND DEEP LEARNING-BASED APPROACHES FOR COVID-19 DISEASE
NDCOV-19 2020 : NEURAL NETWORKS AND DEEP LEARNING-BASED APPROACHES FOR COVID-19 DISEASE

NDCOV-19 2020 : NEURAL NETWORKS AND DEEP LEARNING-BASED APPROACHES FOR COVID-19 DISEASE

Submission Deadline: December 31, 2020


Categories

 
COVID-19


About

Since World War II (WW2), the COVID-19 disease is the big obstacle facing humans. It is very infectious and has affected over 1 million people worldwide. The number of infected cases did not exceed 1,00,000 at the beginning of March 2020. Since then, the number of infections has not only increased exponentially, but also has affected the number of deaths and our way of life, such as the need for social distances. Globally, this issue needs to be tackled urgently. In computer and interactive science, scientists can have observations and guidance as well as new discoveries that can have beneficial implications and results on causes, remedies and analyzes. The latest diagnosis of COVID-19 is based on real-time reverse-transcriptase polymerase chain reaction (RT-PCR) and was regarded as the gold standard for infection confirmation. Neural networks and deep learning techniques can play a significant role in simplifying and accelerating COVID-19 patient diagnosis, delivering high-quality test outcomes, and accurate pro-predictive modeling. This calls for pioneering methods such as neural network, deep learning, artificial intelligence, and machine intelligence as they are very significant. Neural networks and deep learning for COVID-19 disease will give values to scientists in combination with advanced artificial intelligence techniques. We are searching for innovative and unpublished research focused on neural networks, deep learning, and artificial intelligence-based techniques for COVID-19 disease.
 



Credits and Sources

[1] NDCOV-19 2020 : NEURAL NETWORKS AND DEEP LEARNING-BASED APPROACHES FOR COVID-19 DISEASE


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