DETECTION AND CLASSIFICATION OF COVID-19 BY DEEP LEARNING FROM CHEST X-RAYS

The COVID-19 pandemic has highlighted the need for rapid and accurate testing to control the spread of the virus. Chest radiography is an effective method for identifying COVID-19 infections through specific abnormalities observed in infected patients. This research work presents an innovative approach based on convolutional neural networks (CNN) and transfer learning for the detection and classification of COVID-19 from chest X-ray images. We used a dataset including samples classified into three categories: COVID-19, pneumonia and normal cases. By integrating advanced image processing techniques and leveraging the power of artificial intelligence, our model achieved a remarkable accuracy rate. The results obtained demonstrate the effectiveness of our approach to improve the screening and diagnosis of COVID-19, highlighting the potential of AI technologies in the medical field.