Published Paper Details:

The objective of this research paper is to build Covid-19 Detection system using machine Learning so it can reduce the efforts of radiologist can be faster and efficient to carry out final results.as we all know Covid-19 is a rapidly spreading viral disease that infects humans as well as animals are also infected because of this disease. Due to this deadly viral disease The regular life of peoples and the economy of a country are affected . Covid-19 is a normal spreading disease, and till now. These kind of patients are mostly infected from a lung infection after coming in touch with this disease and this has been shown by clinical study of COVID-19 one who infected.For diagnosing of lunge related problem Chest x-ray (i.e., radiography) and chest CT are a more effective imaging technique Still, a substantial chest x-ray is a lower cost process in comparison to chest CT. To provides useful analysis to study a large amount of chest x-ray images that can critically impact on screening of Covid-19 ,Deep learning is the most successful technique used. For covid-19 affected patients as well as healthy patients, for this work We have used the PA view of chest x-ray scans. By applying data after cleaning up the images augmentation, we have used deep learning based CNN models & compared their results. We have compared some Inception V3 and Xception, and ResNeXt models and examined their accuracy. To analyze the model performance, 120 chest x-ray scans samples have been collected from the Kaggle and github, out of which 5007 were used for training and 900 for validation purpose. In result analysis, the Xception model gives the highest accuracy 98% for detecting Chest X-rays images as compared to other models such as Darkcovid. This work only focuses on methods of classifying covid-19 infected patients and does not claim any medical accuracy