We undertook a systematic review of the diagnostic accuracy of artificial intelligence-based
software for identification of radiologic abnormalities (computer-aided detection, or CAD) …

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 …

Importance Interpretation of chest radiographs is a challenging task prone to errors,
requiring expert readers. An automated system that can accurately classify chest …

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 Detection of active pulmonary tuberculosis on chest radiographs (CRs) is
critical for the diagnosis and screening of tuberculosis. An automated system may help …

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 …

BACKGROUND: Tuberculosis (TB) preventive therapy (TPT) decreases the risk of
developing TB disease and its associated morbidity and mortality. The aim of these clinical …

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 …

There have been few independent evaluations of computer-aided detection (CAD) software
for tuberculosis (TB) screening, despite the rapidly expanding array of available CAD …

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 …