Open AccessDiagnosis of COVID-19 Using Chest X-ray
Author(s) -
Sushma Malik,
Sahil Singh,
Narendra Mohan Singh,
Naman Panwar
Publication year - 2021
Publication title -
international journal of informatics, information system and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2810-0670
pISSN - 2775-5584
DOI - 10.34010/injiiscom.v2i1.5347
Subject(s) - covid-19 , radiography , chest radiograph , radiology , medicine , cluster (spacecraft) , presentation (obstetrics) , disease , computer science , pathology , infectious disease (medical specialty) , outbreak , programming language
Covid-19 is also a wide spreading infective agent disease that infects humans. A clinical study of COVID-19 infected patients has shown that these kinds of patients are square measure principally infected from a respiratory organ infection when come in contact with this disease. Chest xray (i.e., radiography) a less complicated imaging technique for identification respiratory organ connected issues. Deep learning is that the foremost undefeated technique of machine learning, that provides helpful analysis to review an oversize quantity of chest x-ray pictures which may critically impact on screening of Covid-19. Throughout this work, we have taken the PA read of chest x-ray scans for covid-19 affected patients conjointly as healthy patients. We have used deep learning-based CNN models and compared their performance. We have equate ResNeXt models and inspect their precision to investigate the model presentation, 6432 chest x-ray scans samples square measure collected from the Kaggle repository. This work solely core on potential ways of cluster covid-19 infected patients.