Globally, the incidence of tuberculosis (TB) is declining very slowly, and the
noncommunicable disease (NCD) burden for many countries is steadily increasing. Several …

The inability to detect all individuals with active tuberculosis has led to a growing interest in
new approaches to improve case detection. Policy makers and program staff face important …

Abstract Background The Xpert MTB/RIF assay has garnered significant interest as a
sensitive and rapid diagnostic tool to improve detection of sensitive and drug resistant …

Predictive artificial intelligence (AI) systems based on deep learning have been shown to
achieve expert-level identification of diseases in multiple medical imaging settings, but can …

Background Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-
related abnormalities on chest radiographs. Various AI algorithms are available …

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 In many countries with a high burden of tuberculosis, most patients receive
treatment in the private sector. We evaluated a multifaceted case-detection strategy in …

Background Globally, TB notifications have stagnated since 2007, and sputum smear
positive notifications have been declining despite policies to improve case detection. We …

Despite 30 years as a public health emergency, tuberculosis (TB) remains one of the world's
deadliest diseases. Most deaths are among persons with TB who are not reached with …

Computer-aided detection (CAD) was recently recommended by the WHO for TB screening
and triage based on several evaluations, but unlike traditional diagnostic tests, software …