Covid 19 Detection from chest X-Ray using CNN

Detecting COVID-19 from chest X-rays using Convolutional Neural Networks (CNNs) has emerged as a promising approach in medical imaging and diagnostics. CNNs, known for their ability to automatically extract features from images, can be trained on large datasets of chest X-rays to differentiate between COVID-19, pneumonia, and healthy lungs. The process involves preprocessing the X-ray images to enhance quality, followed by feeding them into a CNN architecture that consists of multiple layers for feature extraction and classification. By learning patterns associated with the disease, the model can provide rapid and accurate diagnostic support, helping healthcare professionals make informed decisions. This method not only streamlines the detection process but also reduces the burden on healthcare systems, particularly in areas with limited access to testing resources. Overall, the application of CNNs in analyzing chest X-rays represents a significant advancement in the fight against COVID-19.