A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches

In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle epidemic. According recent studies, Machine Learning (ML) has been effectively deployed in sector. Medical imaging sources (radiography computed tomography) have aided development of artificial intelligence(AI) strategies outbreak. As a result, classical machine learning approach detection from Computerized Tomography (CT) images was developed. this study, convolutional neural network (CNN) model feature extraction support vector (SVM) classification axial lung CT-scans into two groups (COVID-19 NonCOVID-19) had proposed. A dataset used is 960 slices CT scan collected Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are study (accuracy, recall, precision, F1 scores). results indicate that proposed generated high-quality dataset, with an overall accuracy 98.95% recall 97 %.