trauma

CE
fda

AZtrauma is the most widely used AI software for detecting fractures, dislocations, and joint effusions on X-rays. Clinically validated by top institutions on all continents, AZtrauma ensures trust and reliability in acute situations.

AZtrauma is the most widely used AI software for detecting fractures, dislocations, and joint effusions on X-rays. Clinically validated by top institutions on all continents, AZtrauma ensures trust and reliability in various medical settings.

Pathologies Detected

Anatomical Areas Covered
UPPER LIMB
SPINE
RIB CAGE
PELVIS
LOWER LIMB

Backed by Clinical Research

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Studies

Benefits

Optimized Workflow and Improved Quality of Care

Studies made on more than 150 000 patients in 200 centers shows tremendous ROIs.
67%
False Negatives
Avoided per Case
83%
Turnaround Time (TAT) Reduction

Readers AUC Increased

Studies show significant improvement in readers' accuracy, with an Area Under the Curve (AUC) increasing from 0.84 to 0.89

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 Michaely
Owner and Chief Radiologist MVZ Radiologie Karlsruhe

The implementation of AZmed's Rayvolve AI software for fracture detection at our institution has particulary helped our junior clinicians and practicioners in the emergency department, especially out of hours with additonal 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 Basu
MSK radiologist at Wrightington Hospital

Rayvolve 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, MD,
MSK radiologist at UH

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