Background Digital chest X-ray (dCXR) computer-aided detection (CAD) technology uses
lung shape and texture analysis to determine the probability of tuberculosis (TB). However …

BACKGROUND: DetecTB (Diagnostic Enhanced Tools for Extra Cases of TB), an intensified
tuberculosis (TB) case-finding programme targeting prisons and high-risk communities was …

Rationale: Realizing the Global Plan to End Tuberculosis (TB) will require reaching at least
90% of people in key populations, such as inmates, through optimizing case-finding …

Background Optimized tuberculosis (TB) screening in high burden settings is essential for
case finding. We evaluated digital chest X-ray with computer-aided detection (CAD) software …

Tuberculosis (TB) transmission in healthcare facilities is common in high-incidence
countries. Yet, the optimal approach for identifying inpatients who may have TB is unclear …

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 …

Background In settings without access to rapid expert radiographic interpretation, artificial
intelligence (AI)–based chest radiograph (CXR) analysis can triage persons presenting 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 …

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

SETTING: A busy urban health centre in Lusaka, Zambia. OBJECTIVE: To compare the
accuracy of automated reading (CAD4TB) with the interpretation of digital chest radiograph …