Solving the Radiology Challenge AI Visions

What if our vision could improve your focus?
For healthcare professionals and relevant decision makers.
Why AI in Radiology?
It’s no secret that ever-increasing pressure is creating significant challenges for radiologists and hospitals, which also affects patient care. Today, the industry is seeing:
chevronGreater complexity, with 5x more images
produced per scan
chevronHigh stress, with 49% of radiologists reporting
signs of burnout
chevronDiagnostic errors, with approximately 40 million
per year related to imaging, worldwide.
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1McDonald, Schwartz, Eckel et al., 2015, The Effects of Changes in Utilization and Technological Advancements of Cross-Sectional Imaging on Radiologist Workload, Academic Radiology, 22(9), 1191-1198
2Kane, L. (2022) Medscape National Physician Burnout & Suicide Report 2022: The Generational Divide. Medscape Retrieved June 22, 2022 from 6014664?reg=1#2
3Itri, J. N., Tappouni, R. R., McEachern, R. O., Pesch, A. J., Patel, S. H. (2018) Fundamentals of Diagnostic Error in Imaging. RadioGraphics 38, 1845-1865. Retrieved June 8, 2022 from *
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