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Chest X-rays remains to be the most common imaging modality used to diagnoselung diseases. However, they necessitate the interpretation of experts(radiologists and pulmonologists), who are few. This review paper investigatesthe use of deep transfer learning techniques to detect COVID-19, pneumonia, andtuberculosis in chest X-ray (CXR) images. It provides an overview of currentstate-of-the-art CXR image classification techniques and discusses thechallenges and opportunities in applying transfer learning to this domain. Thepaper provides a thorough examination of recent research studies that used deeptransfer learning algorithms for COVID-19, pneumonia, and tuberculosisdetection, highlighting the advantages and disadvantages of these approaches.Finally, the review paper discusses future research directions in the field ofdeep transfer learning for CXR image classification, as well as the potentialfor these techniques to aid in the diagnosis and treatment of lung diseases.

Deep transfer learning for detecting Covid-19, Pneumonia and Tuberculosis using CXR images -- A Review