Before revision:  The areas under the receiver operating characteristic curves are qXR: 0.91 (95\% CI: 0.90-0.91), Lunit INSIGHT CXR: 0.89 (95\% CI: 0.88-0.89), InferReadDR: 0.85 (95\% CI: 0.84-0.86), JF CXR-1: 0.85 (95\% CI: 0.84-0.85) , CAD4TB: 0.82 (95\% CI: 0.81-0.83). We also proposed a new analytical framework that evaluates a screening and triage test and informs threshold selection through tradeoff between cost efficiency and ability to triage. Further, we assessed the performance of the five AI algorithms across the subgroups of age , use cases, and prior TB history , and found that the threshold scores performed differently across different subgroups.
After revision:  The areas under the receiver operating characteristic curves are qXR: 0.91 (95\% CI: 0.90-0.91), Lunit INSIGHT CXR: 0.89 (95\% CI: 0.88-0.89), InferReadDR: 0.85 (95\% CI: 0.84-0.86), JF CXR-1: 0.85 (95\% CI: 0.84-0.85) , CAD4TB: 0.82 (95\% CI: 84.26-85.53\%). Only qXR met the TPP with 74.3\% specificity at 90\% sensitivity. Five AI algorithms can reduce the number of Xpert tests required by 50\%, while maintaining a sensitivity above 90\%. All AI algorithms performed worse among the older age and people with prior TB history , and found that the threshold scores performed differently across different subgroups.