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Investigation and Comparison of Effective Machine Learning Algorithms in order to Improve the Prediction of Corona Virus Behavior
Volume 2, Issue 1, 2020, Pages 14 - 24
1 Teacher of Shamsipour Technical University, Tehran, Iran
2 uyi
3 Teacher of Shamsipour Technical University, Tehran, Iran
4 Technical and Vocational University, Tehran, Iran
Abstract :
Covid-19 virus has been affecting people's lives as an acute respiratory disease since late 2019. For this reason, it has become a key topic for IT professionals. Therefore, the concept of machine learning and deep learning can help a lot in controlling this virus. However, different methods of machine learning and deep learning patterns for predicting viral behavior such as mortality data and CT images of the scanned disease have been investigated. In this paper, according to the review of algorithms and work done in this field, the most optimal algorithm for predicting viral behavior in the human body has been identified. Also, these algorithms are compared and categorized based on virus detection. The results show that most of the data used were CT scan images of corona disease patients. Also, these researches have been analyzed in order to use machine learning algorithms, deep learning and neural networks. In addition, in the field of pattern recognition in this area, the most optimal algorithms are related to classical machine learning. Finally, experiments show that the best algorithm for diagnosing corona disease behavior is Naïve Bayes and SVM.
Covid-19 virus has been affecting people's lives as an acute respiratory disease since late 2019. For this reason, it has become a key topic for IT professionals. Therefore, the concept of machine learning and deep learning can help a lot in controlling this virus. However, different methods of machine learning and deep learning patterns for predicting viral behavior such as mortality data and CT images of the scanned disease have been investigated. In this paper, according to the review of algorithms and work done in this field, the most optimal algorithm for predicting viral behavior in the human body has been identified. Also, these algorithms are compared and categorized based on virus detection. The results show that most of the data used were CT scan images of corona disease patients. Also, these researches have been analyzed in order to use machine learning algorithms, deep learning and neural networks. In addition, in the field of pattern recognition in this area, the most optimal algorithms are related to classical machine learning. Finally, experiments show that the best algorithm for diagnosing corona disease behavior is Naïve Bayes and SVM.
Keywords :
Machine Learning, Deep Learning, Neural networks, Corona virus, Pattern Recognition.
Machine Learning, Deep Learning, Neural networks, Corona virus, Pattern Recognition.