How it works

Pioneering artificial intelligence in healthcare

At we utilise cutting-edge science to pioneer new forms of diagnostic medicine; this revolutionary approach to healthcare is a step change in the treatment and prevention of diseases, benefiting patients on a global scale.

Deep learning

Our red dot® algorithm is based on state-of-the-art deep learning models. Thanks to their specific architecture and ability to model complex functions, deep learning models have proved to be extremely efficient at processing images. Our red dot® algorithm was trained on over 30,000 CXRs with detailed annotations from certified radiologists. The training process teaches the algorithm to both classify a CXR and localize its findings. This localization is rendered through heatmaps and allows to understand and interpret red dot® output.

Watch the video to see it in action

Seamless integration

Using standard HL7 and DICOM messaging, the red dot® platform will retrieve, receive and process each CXR examination at the point of acquisition and send an electronic notification back to the Trust RIS (or PACS in a PACS driven reporting scenario) to indicate whether the examination is normal, or whether an abnormality has been indicated.  This notification will prioritise the examination within the existing reporting worklists for urgent reporting.  Messaging and CXR images are received via secure encrypted VPN to the red dot® platform, via the AI Gateway from the Trust RIS/PACS. All patient examination data resides in fully NHS accredited data centres

Our red dot® platform can seamlessly integrate
with your existing PACS/RIS setup

Our AI Technology is in use today

“’s AI technology is specifically designed to support our skilled radiology workforce by understanding and supporting their existing workflows and enabling them to manage reporting more efficiently.”

Neil Perry
Associate Director Digital Transformation
Dartford and Gravesham NHS Trust

“The Behold red dot® algorithm shows tremendous potential in prioritisation of CXRs requiring a CT for suspected lung cancer.”

Dr Indrajeet Das & Dr Jan Brozik
Consultant Radiologists
University of Leicester Hospitals NHS Trust

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If you want to see more, sign up for our free demo using your hospital email address.