What is CalanticTM Digital Solutions?
An orchestrated suite of AI radiology solutions that will focus on quality of care today and help transform radiology tomorrow. Our cloud-based marketplace, with service line AI apps, are integrated into the radiologist’s workflow with the Calantic Viewer integrated in the PACS viewport.
For any queries, please contact DigitalsolutionsANZ@bayer.com
What is Calantic
Why Calantic?
Calantic gives radiologists access to tools and AI applications, that support worklist prioritization, detection and quantification– with intuitive functionality tailored for specific disease areas.
Seamless workflow integration
Within your PACS environment, for easy access to an orchestrated set of AI applications that empower how you work.
Improving your efficiency and diagnostic accuracy
By automating tasks, flagging time critical and/or incidental findings. Minimize the risks of false negatives and have more time to focus on diagnosis.
A trusted partner
With clinical expertise and the infrastructure to provide data security protection, technical support, educational resources, and only clinically approved medical image analysis applications.
Ever increasing pressure on healthcare is threatening the sustainability of radiology departments and patients
GREATER COMPLEXITY
5x
Increase
In the number of images produced per scan1
RADIOLOGY DEPARTMENTS PUSHED TO THEIR LIMITS
49%
Radiologists
reporting signs of burn-out2
DIAGNOSTIC ERRORS
~40m
Diagnostic Errors
per year worldwide3
How Calantic works
Developed by radiologists for radiologists, Calantic takes previous fragmented and unrelated app solutions and coordinates them into a single convenient marketplace. Vetted with Bayer's expertise, to ensure the feasibility and reliability of third-party solutions.
Featured App
The Calantic Thoracic package is a selection of AI apps supporting efficient detection of potential Thoracic pathologies. One of them is ClearReadTM CT. This AI application can improve detection by highlighting suspicious nodules*.
Our App Collaborators include
References
1McDonald, RJ, Schwartz, K, Eckel, L. 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 August 17, 2022 from https://www.medscape.com/slideshow/2022-lifestyle-burnout-6014664?reg=1#2
3Itri, J. N., Tappouni, R. R., McEachern, R. O., et.al. (2018) Fundamentals of Diagnostic Error in Imaging. RadioGraphics 38, 1845-1865. Retrieved August 17, 2022 from https://pubs.rsna.org/doi/epdf/10.1148/rg.2018180021
