Kloska, AnnaTarczewska, MartynaGiełczyk, AgataMarciniak, Beata2023-09-252023-09-252023Kloska A., Tarczewska M., Giełczyk A., Marciniak B., Lung Xray Images Analysis for COVID-19 Diagnosis. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 485-489, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.77.978-83-66741-92-8http://hdl.handle.net/11652/4853https://doi.org/10.34658/9788366741928.77Background: The SARS-CoV-2 pandemic began in early 2020. It paralyzed human life all over the world and threatened our security. Thus, proposing some novel and effective approaches to diagnosing COVID-19 infections became paramount. Methods: This article proposes a method for the classification of chest X-ray images based on the transfer learning. We examined also different scenarios of dataset augmentation. Results: The paper reports accuracy=98%, precision=97%, recall=100% and F1-score=98% in the most promising approach. Conclusion: Our research proofs that machine learning can be used in order to support medics in chest X-ray classification and implementing augmentation can lead to improvements in accuracy, precision, recall, and F1-scores.enDla wszystkich w zakresie dozwolonego użytkuFair use conditionCOVID-19image processingaugmentationartificial intelligenceCOVID-19przetwarzanie obrazuwzmacnianiesztuczna inteligencjaRozdział - monografiaLicencja PŁLUT License10.34658/9788366741928.77