SCOTTSDALE, AZ. May 21, 2026 — A landmark, peer-reviewed global study representing the largest published evaluation of artificial intelligence in X-ray imaging has been published in Radiography, analyzing 258,373 X-rays from 100 medical centers across 26 countries and five continents. The study was led by Dr. Sean Raj, Chief Medical Officer and Chief Innovation Officer at SimonMed, who served as senior author.
SimonMed, one of the largest outpatient imaging providers in the United States, contributed U.S. clinical data and played a central role in the study’s design, execution, and analysis, reinforcing its leadership in the clinical validation of artificial intelligence in radiology.
The study evaluated all four components of the Rayvolve® AI Suite as a unified clinical platform under real-world conditions, with no exclusions based on image quality or acquisition protocol. The system demonstrated high diagnostic performance across multiple use cases, including musculoskeletal trauma, chest imaging, automated measurements, and bone age assessment. AZtrauma achieved an AUC of 98.3% (sensitivity: 97.4%, specificity: 96.4%) across 195,706 musculoskeletal examinations. AZchest demonstrated an AUC of 97.8% (sensitivity: 96.7%, specificity: 87.9%) across 61,418 chest radiographs covering six pathology categories. AZmeasure and AZboneage delivered measurement precision within 1.83 degrees for angles, 1.1 mm for lengths, and a bone age estimation error of approximately six months.
Performance remained consistent across pathologies, anatomies, patient demographics, and global care settings, with all 258,373 images processed without a single technical failure, highlighting both the robustness and scalability of AI in real-world clinical environments.
SimonMed’s contribution to the study builds on a partnership that has deepened since 2023, when SimonMed selected AZmed as its AI partner for X-ray diagnostics following an independent evaluation across its outpatient network. That initial deployment demonstrated a 6x reduction in turnaround time for fracture cases and 98.5% sensitivity across SimonMed centers. SimonMed subsequently provided the clinical data that supported AZmed’s 2024 FDA 510(k) clearance for pediatric fracture detection. The inclusion of SimonMed’s U.S. imaging data in this 26-country study extends the collaboration from operational deployment and regulatory contribution to large-scale, independently published clinical evidence.
“Validating a complete AI suite at this scale, across 100 centers in 26 countries, establishes a new standard for clinical evidence in radiology AI,” said Julien Vidal, CEO of AZmed. “SimonMed’s contribution at every stage of this journey, from early U.S. deployment through FDA clearance and now the largest published X-ray AI study, reflects the kind of clinical partnership that advances the entire field.”
“This study represents a defining moment for AI in medical imaging,” said Dr. Sean Raj, Chief Medical Officer and Chief Innovation Officer at SimonMed. “We are proud to have led a global effort that not only validates AI performance at an unprecedented scale, but also reinforces the importance of rigorous, real-world clinical evidence. We are committed to continue our founding mission – to deliver high quality, accessible care at scale while measurably improving diagnostic quality for our radiologists and the patients they serve.”
The study is available in Radiography.