The global tuberculosis burden remains substantial, with more than 10 million people newly
ill per year. Nevertheless, tuberculosis incidence has slowly declined over the past decade …

There has been an explosive growth in research over the last decade exploring machine
learning techniques for analyzing chest X-ray (CXR) images for screening cardiopulmonary …

Deep learning (DL) neural networks have only recently been employed to interpret chest
radiography (CXR) to screen and triage people for pulmonary tuberculosis (TB). No …

Background Deep learning-based radiological image analysis could facilitate use of chest x-
rays as triage tests for pulmonary tuberculosis in resource-limited settings. We sought to …

Background The World Health Organization (WHO) recommends chest radiography to
facilitate tuberculosis (TB) screening. However, chest radiograph interpretation expertise …

Background Automated radiologic analysis using computer-aided detection software (CAD)
could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence …

OBJECTIVE: To systematically review the diagnostic accuracy of computer-aided detection
(CAD) of pulmonary tuberculosis (PTB) on digital chest radiographs (CXR). DESIGN: We …

In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active
pulmonary tuberculosis (PTB) screening when interpreted by human readers. However, they …

Background Migrants account for a large and growing proportion of tuberculosis (TB) cases
in low-incidence countries in the European Union/European Economic Area (EU/EEA) …

Recently, the number of artificial intelligence powered computer-aided detection (CAD)
products that detect tuberculosis (TB)-related abnormalities from chest X-rays (CXR) …