From abnormality detection to decision-grade deployment: Strengthening the next translational step for DeepCXR

We read with great interest the recent IJMR article by Abhishek et al 1 describing DeepCXR v1.1, an artificial intelligence (AI)-driven ensemble model for comprehensive chest X-ray abnormality detection and deployment.This work is timely and important because it moves beyond a narrow proof-of-concept development toward real-world implementation in a high-burden setting.Overall, the next benchmark for the field is not broader deployment alone, but deployment that is transparent, monitored, equitable, and demonstrably linked to patient-important and system-level outcomes.