Optimizing Implementation of Digital X-ray with Computer-Aided Detection for Community-Based Tuberculosis Screening
Date:
08/29/2024
Locations:
Lead Investigators:
Summary
Computer-aided detection (CAD), which uses artificial intelligence to analyze chest X-rays, is now WHO- recommended for tuberculosis (TB) screening and holds the potential to improve TB detection in high-burden, low-resource communities. This research seeks to evaluate the adaptive application of CAD for community-based TB screening in sub-Saharan Africa, utilizing individualized and context-specific methods, as an alternative to the current standard of a "one-size-fits-all" approach. By assessing diagnostic accuracy, implementation barriers, and cost-effectiveness of each screening strategy, the insights gained from this study could be used to facilitate earlier detection of TB and reduce the high morbidity and mortality caused by tuberculosis.