Human adult female right hand bones x-ray image. Medical and anatomy radiography or imagery.

BoneView Trauma CE2797

Your AI companion for bone trauma X-Rays

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22

Countries

Deployed with various IT infrastructures

5000

Users

Radiologists, Emergency Physicians, radiographers...

+ 550

Hospitals and clinics

Using the solution in clinical routine

Clinically Validated

Radiologists need medical grade solutions they can trust.

MDR CE certified Class IIa & FDA cleared

Companioning more than 1500 users

BoneView Trauma AI provides radiologists and ED doctors with an instant and automatic 2nd reading of trauma X-Rays fully integrated in the reading workflow.

Save time and improve reading comfort

Reduce medical errors and improve diagnostic accuracy

Reduce claims and associated costs

" As an academic radiologist, I was routinely impressed with BoneView's AI algorithms, which allow detection of subtle abnormalities and improved diagnostic sensitivity, specificity and accuracy. Additionally, the software seamlessly integrated into any workflow, saved time and increased efficiency for the radiologist. "

Pr. Ali Guermazi, MD - Boston university

“ Gleamer's BoneView AI is to date the most stable and most robust solution on the AI market, the results are outstanding ”

Prof. Dr. med. Dr. rer. medic. Stefan M. Niehues, MHB La Charité, Berlin, Germany

" In a context in which exam workload is getting higher, AI allows us to reduce human errors: perception, satisfaction of search, side biases... "

Romain Malezieux, Radiologist, France

" BoneView Trauma integrates seamlessly into our daily workflow. Our working comfort was improved by this automatic and instantaneous second reading. BoneView Trauma enables us to save time and improve patient care. "

Aurélien Lambert, Radiologist, France

" Radiologists must manage their workflow in a constrained environment. By securing diagnosis and limiting the number of undescribed fractures, BoneView Trauma is a precious tool in everyday work and a shield against potential litigation procedures. "

Jean-Claude Le Van An, Radiologist, France

" This study (Duron et. al, Radiology 2021) is the result of significant collaborative work between specialists in radiology, data science, biostatistics, and GLEAMER teams to evaluate the clinical performance of BoneView Trauma. This is an important step that quantifies and scientifically validates the benefits of this AI solution available to healthcare institutions, in a context where several solutions are marketed without published objective results "

Antoine Feydy, Radiologist, France

Already Trusted By

AI-powered workflow

BoneView Trauma is Class IIa medical devices manufactured by Gleamer and whose conformity assessment has been carried out by the notified body BSI CE 2797 relatively to the 2017/745 regulation. It is a software using deep learning techniques intended to provide preliminary data for helping clinicians’ diagnosis of X-ray radiographs. Please read the operating instructions carefully.

Instant findings for safer and faster interpretation

Use BoneView Trauma as a double check and avoid missing tiny lesions. BoneView Trauma detects fractures, effusions, dislocations, and bone lesions on X-Ray images.

- 30 %

Missed fractures*

Smart worklist for triage and prioritization

Use BoneView Trauma to triage and prioritize interpretations. BoneView supports integration with RIS through HL7 capability.

Full workflow integration

BoneView Trauma integrates seamlessly with all IT infrastructures and communicates with the PACS to process appropriate examinations and display results in the user's usual environment.


Related Evidence

BoneView Trauma
  • Duron et al.,
  • Radiology

Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study

  • Omoumi et. al,
  • European Radiology

To buy or not to buy—evaluating commercial AI solutions in radiology (the ECLAIR guidelines)

Clinical cases

Make up your mind and navigate among real-life examples

Removing satisfaction of search bias

by consistently detecting all fractures

Indication
41 year-old male after a motorcycle accident

Results with BoneView
Fracture of the collar bone and fracture of the rib that could have easily been missed

Increasing sensitivity

By detecting subtle fractures

Indication
30 y.o. woman limping. Crush trauma a week ago (domestic violence)

Results with BoneView
Fracture of the fourth metatarsal bone

Human adult female right hand bones x-ray image. Medical and anatomy radiography or imagery.

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