Automated classification of chest X-rays: a deep learning approach with attention mechanisms.

Journal: BMC medical imaging
PMID: 40038588

Abstract

BACKGROUND: Pulmonary diseases such as COVID-19 and pneumonia, are life-threatening conditions, that require prompt and accurate diagnosis for effective treatment. Chest X-ray (CXR) has become the most common alternative method for detecting pulmonary diseases such as COVID-19, pneumonia, and lung opacity due to their availability, cost-effectiveness, and ability to facilitate comparative analysis. However, the interpretation of CXRs is a challenging task.

Authors

  • Burcu Oltu
    Department of Biomedical Engineering, Baskent University, Etimesgut, Ankara, 06790, Türkiye. boltu@baskent.edu.tr.
  • Selda Güney
    Department of Electrical and Electronics Engineering, Baskent University, Etimesgut, Ankara, 06790, Türkiye.
  • Seniha Esen Yuksel
    Department of Electrical and Electronics Engineering, Hacettepe University, Beytepe, Ankara, 06800, Türkiye.
  • Berna Dengiz
    Department of Industrial Engineering, Baskent University, Etimesgut, Ankara, 06790, Türkiye.

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