Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images

• Published in: Journal of imaging Vol. 10; no. 2; p. 45
• Main Authors: Chatterjee, Soumick, Saad, Fatima, Sarasaen, Chompunuch, Ghosh, Suhita, Krug, Valerie, Khatun, Rupali, Mishra, Rahul, Desai, Nirja, Radeva, Petia, Rose, Georg, Stober, Sebastian, Speck, Oliver, Nürnberger, Andreas
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.02.2024
• Subjects: Accuracy; Artificial intelligence; Back propagation; chest X-ray; Classification; Computed tomography; Computer-aided medical diagnosis; Coronaviruses; COVID-19; Decision making; Deep learning; Disease transmission; Image classification; Infections; Machine learning; Medical imaging; Methods; model ensemble; multilabel image classification; Occlusion; Pneumonia; Tuberculosis; X ray imagery; Germany; COVID-19; deep learning; interpretability analysis; multilabel image classification; pneumonia; model ensemble; chest X-ray

The outbreak of COVID-19 has shocked the entire world with its fairly rapid spread, and has challenged different sectors. One of the most effective ways to limit its spread is the early and accurate diagnosing of infected patients. Medical imaging, such as X-ray and computed tomography (CT), combine...