How Can a Deep Learning Algorithm Improve Fracture Detection on X-rays in the Emergency Room?

AZboneage is AZmed’s CE-marked AI software that assists healthcare professionals in estimating skeletal maturity in pediatric patients by analyzing hand radiographs using the Greulich and Pyle method.

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The algorithm generates structured outputs, which display the predicted skeletal age and the recorded chronological age when available. The system displays results through a secondary diagnostic report, preserving the original radiographic image and allowing for auditability and diagnostic consistency.

AZmed, one of the leading AI radiology companies, and Nexus-MD, a U.S.-based leader in imaging data infrastructure, have announced a new commercial agreement. Nexus-MD will introduce AZmed's FDA-cleared tools, AZtrauma and AZchest, to its U.S. network of healthcare providers. The partnership is intended to resolve an enduring operational problem in radiology, which involves speeding up diagnostic workflows without raising the burden on clinicians.

O atendimento ao trauma nos departamentos de emergência depende da detecção rápida e precisa de fraturas para aliviar a dor do paciente e evitar complicações graves. É nesse ponto que a inteligência artificial (IA) se tornou uma ferramenta transformadora que otimiza lo processo de diagnóstico e permite um fluxo de trabalho clínico contínuo.