Diffuse cystic lung disease caused by tuberculosis infection: Case series

Wang, Lu; Liu, Jingwei; Yang, Huahong; Peng, Liping

doi:10.1016/j.jiph.2023.02.013

Cited by 3 publications

(1 citation statement)

References 33 publications

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“…These lung conditions: Covid-19, Pneumonia, and Tuberculosis have serious health consequences and can be fatal if untreated or mismanaged. However, misdiagnosis [13], shortage of healthcare professionals [14], and the high cost of treatment [15] continue to be significant challenges. To begin with, lung diseases can be difficult to accurately diagnose, particularly in the early stages, and are frequently misdiagnosed as other respiratory conditions, causing disease progression by delaying proper treatment.…”

Section: Background Informationmentioning

confidence: 99%

Deep Transfer Learning for Detecting Covid-19, Pneumonia and Tuberculosis Using Cxr Images – A Review

2023

COVID Res OA

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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 classification, as well as the potential for these techniques to aid in the diagnosis and treatment of lung diseases.

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Section: Background Informationmentioning

confidence: 99%