Background Tuberculosis (TB) was the leading infectious cause of mortality globally prior to
COVID-19 and chest radiography has an important role in the detection, and subsequent …

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

The high mortality rate in Tuberculosis (TB) burden regions has increased significantly in the
last decades. Despite the possibility of treatment for TB, high burden regions still suffer …

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 …

Tuberculosis (TB) is the leading cause of preventable death in HIV-positive patients, and yet
often remains undiagnosed and untreated. Chest x-ray is often used to assist in diagnosis …

As a major infectious disease, tuberculosis (TB) still poses a threat to people's health in
China. As a triage test for TB, reading chest radiography with traditional approach ends up …

Tuberculosis is an infectious disease caused by a widely spread microbe called
Mycobacterium tuberculosis (MTB). Tuberculosis (TB) detection with chest x-ray images is …

Tuberculosis (TB) is an infectious disease affecting humans' lungs and is currently ranked
the 13th leading cause of death globally. Due to advancements in technology and the …

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 …

Purpose To evaluate the efficacy of deep convolutional neural networks (DCNNs) for
detecting tuberculosis (TB) on chest radiographs. Materials and Methods Four deidentified …