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April 1, 2020The International Journal of Tuberculosis and Lung Disease

Computer-aided detection for tuberculosis and silicosis in chest radiographs of gold miners of South Africa

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Authors

CYC. YoungSBStephen BarkerRERodney Ehrlich

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Overview

Randomized trial evaluates CAD's ability to detect TB and silicosis in gold miners, suggesting potential for mass screening.

Key Points

  • This study aims to evaluate the effectiveness of computer-aided detection (CAD) systems in identifying tuberculosis (TB) and silicosis in chest radiographs (CXRs) of gold miners.
  • Analyzed 330 CXRs with expert classifications of diseases such as silicosis and TB.
  • Four health technology companies tested their CAD systems for disease prediction accuracy.
  • Used receiver operating characteristic curve analysis to assess the CAD systems' performance.
  • Three CAD systems accurately differentiated TB from normal images.
  • Two CAD systems accurately differentiated silicosis from normal images.
  • The top-performing system achieved a sensitivity and specificity of 98.2% for distinguishing abnormal from normal CXRs.

Cite This Study

Young et al. (2020) studied this question.

synapsesocial.com/papers/6a15537415658026c0823456https://doi.org/10.5588/ijtld.19.0624
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Also Consider

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  4. 4Diagnostic accuracy of Chest X-Ray Computer Aided Detection software and blood biomarkers for detection of prevalent and incident tuberculosis in household contacts followed up for 5 years2024 · 1 citations
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