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Validation of Artificial Intelligence Enabled TB Screening and Diagnosis in Zambia

NCT05139940 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 2432

Last updated 2025-05-15

No results posted yet for this study

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

Sponsors & Collaborators

  • Centre for Infectious Disease Research in Zambia

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-11-22
Primary Completion
2022-09-30
Completion
2022-11-30

Countries

  • Zambia

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05139940 on ClinicalTrials.gov