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Clinical Trial Summary

Tuberculosis (TB) is a global epidemic and for many years has remained a major cause of death throughout the developing world. Zambia is among the top 30 TB/HIV high burden countries. Chest X-ray (CXR) is recommended as a triaging test for TB, and a diagnostic aid when available. However, many high-burden settings lack access to experienced radiologists capable of interpreting these images, resulting in mixed sensitivity, poor specificity, and large inter-observer variation. In recognition of this challenge, the World Health Organization has recommended the use of automated systems that utilize artificial intelligence (AI) to read CXRs for screening and triaging for TB. In this study, we primarily evaluate the performance of our AI algorithm for TB, and secondarily for Abnormal/Normal.


Clinical Trial Description

n/a


Study Design


Related Conditions & MeSH terms


NCT number NCT05139940
Study type Observational
Source Centre for Infectious Disease Research in Zambia
Contact Monde Muyoyeta, MBChB,PhD
Phone +260966765615
Email monde.muyoyeta@cidrz.org
Status Recruiting
Phase
Start date November 22, 2021
Completion date November 30, 2022

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