Trials / Completed
CompletedNCT05139940
Validation of Artificial Intelligence Enabled TB Screening and Diagnosis in Zambia
- Status
- Completed
- Phase
- —
- Study type
- Observational
- Enrollment
- 2,432 (actual)
- Sponsor
- Centre for Infectious Disease Research in Zambia · Academic / Other
- Sex
- All
- Age
- 18 Years
- Healthy volunteers
- Not accepted
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.
Conditions
Timeline
- Start date
- 2021-11-22
- Primary completion
- 2022-09-30
- Completion
- 2022-11-30
- First posted
- 2021-12-01
- Last updated
- 2025-05-15
Locations
3 sites across 1 country: Zambia
Source: ClinicalTrials.gov record NCT05139940. Inclusion in this directory is not an endorsement.