An Efficient CNN Model for COVID-19 Disease Detection Based on X-Ray Image Classification

• Published in: Complexity (New York, N.Y.) Vol. 2021; no. 1
• Main Authors: Reshi, Aijaz Ahmad, Rustam, Furqan, Mehmood, Arif, Alhossan, Abdulaziz, Alrabiah, Ziyad, Ahmad, Ajaz, Alsuwailem, Hessa, Choi, Gyu Sang
• Format: Journal Article
• Language: English
• Published: Hoboken Hindawi 2021; John Wiley & Sons, Inc; Wiley
• Subjects: Accuracy; Algorithms; Artificial intelligence; Artificial neural networks; Chest; Classification; Computational linguistics; Coronaviruses; COVID-19; Data mining; Datasets; Deep learning; Design; Diseases; Image analysis; Image classification; Image quality; Language processing; Lung diseases; Lungs; Machine learning; Medical diagnosis; Medical imaging; Medical research; Model testing; Natural language interfaces; Neural networks; Pandemics; Pneumonia; Radiation; Severe acute respiratory syndrome coronavirus 2; X-rays

Artificial intelligence (AI) techniques in general and convolutional neural networks (CNNs) in particular have attained successful results in medical image analysis and classification. A deep CNN architecture has been proposed in this paper for the diagnosis of COVID-19 based on the chest X-ray imag...