Journal of Lung Diseases & Treatment

Department of Computer Science, Dedan Kimathi University of Technology, Nyeri, Kenya

Publications

• Review Article   
  Deep Transfer Learning for Detecting COVID-19, Pneumonia and Tuberculosis using CXR Images: A Review
  Author(s): Irad Mwendo*, Patrick Gikunda and Anthony Maina
  
  Chest X-rays remains to be the most common imaging modality used to diagnose lung diseases. However, they necessitate the interpretation of experts (radiologists and pulmonologists), who are few. This review paper investigates the use of deep transfer learning techniques to detect COVID-19, pneumonia and tuberculosis in Chest X-Ray (CXR) images. It provides an overview of current state of the art CXR image classification techniques and discusses the challenges and opportunities in applying transfer learning to this domain. The paper provides a thorough examination of recent research studies that used deep transfer learning algorithms for COVID-19, pneumonia and tuberculosis detection, highlighting the advantages and disadvantages of these approaches. Finally, the review paper discusses future research directions in the field of deep transfer learning for CXR image cl.. Read More»
  DOI: 10.37421/2472-1018.2023.9.180

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