AZchest: AI Chest Detection
AZchest is a best-in-class AI radiology solution that interprets chest X-rays, automatically identifying, triaging, and generating reports for a wide range of abnormalities across the lungs, heart, and ribs. Trusted by leading healthcare institutions worldwide, AZchest delivers consistent performance across your entire chest X-ray volume.
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Pathologies detected
Anatomical coverage: Rib cage · Lungs · Heart
Clinical studies
The world's largest X-ray AI study
We evaluated Rayvolve, our flagship X-ray AI suite, in the largest peer-reviewed multicenter study of its kind, spanning real-world clinical settings on five continents.
Worldwide standalone performance
Cohen et al. (2026), Radiography. Dual-reader consensus across 61,418 chest radiographs, six pathology categories.
Built on clinical evidence
AZmed's Rayvolve and Rayscan AI suites are rigorously validated with world-leading institutions across a broad range of imaging modalities. Based on peer-reviewed clinical literature and large-scale real-world studies, AZmed's software provides high-quality image interpretation and reliable decision support, driving better patient care and raising the bar for safer, more sustainable radiology.
Optimized workflow and improved quality of care
Validated on more than 9,000 cases across 15 centers.
+11.4%
Sensitivity per case
-35.8%
Reading time decreased
AZchest AUC per abnormality
Studies show high and consistent performance, with area under the curve (AUC) between 0.913 and 0.958.
Testimonials
We use Rayvolve for the detection of fractures and thoracic pathologies. The solution seamlessly integrates into our local PACS and our workflow. Thanks to its results, our radiologists can significantly speed up their overall reporting while simultaneously increasing its accuracy. We therefore consider it our AI-based second opinion, which boosts our overall quality and performance.
Henrik MichaelyOwner & Chief RadiologistMVZ Radiologie KarlsruheThe implementation of AZmed’s Rayvolve AI software for fracture detection at our institution has particularly helped our junior clinicians and practitioners in the emergency department, especially out of hours — with additional support in image interpretation and diagnosis, which in turn allows for a more efficient and streamlined patient treatment pathway into Orthopaedic fracture clinic.
Dr Subhasis BasuMSK RadiologistWrightington HospitalRayvolve demonstrated high stand-alone accuracy, aided diagnostic accuracy, and decreased interpretation time. When extrapolated over an entire population, one can see quickly how using this tool can really help decrease medical errors and healthcare costs.
Navid Faraji, MDMSK RadiologistUHOther AI radiology solutions
Support every diagnostic
read with artificial intelligence
Book a custom demo. Our team will show you how AI results appear in your viewer, how AZmed integrates with your PACS, and what a typical implementation involves.
