MedyMatch Technology unveils artificial intelligence tehnology for intracranial bleed detection

23 November 2016 (Last Updated November 23rd, 2016 18:30)

Israel-based deep learning and artificial intelligence company MedyMatch Technology has unveiled its artificial intelligence (AI) based technology to detect the presence of intracranial hemorrhage or brain bleed occurring during brain trauma and stroke.

Israel-based deep learning and artificial intelligence company MedyMatch Technology has unveiled its artificial intelligence (AI) based technology to detect the presence of intracranial hemorrhage or brain bleed occurring during brain trauma and stroke.

The new technology is expected to be used in a patient specific computer assisted detection (CAD) tool used by physicians in the emergency room to aid the detection of intracranial bleeds.

It will also come to the marketplace in a prioritisation algorithm operating within a PACS or on a CT to help prioritise cases based on the potential presence of a bleed and as a tool to educate people to proactively identify bleed cases.

"Our platform and AI approach will facilitate rapid decision support development, clinical discovery and propel MedyMatch into adjacent decision support opportunities."

MedyMatch CEO and chairman Gene Saragnese said: "The generalised 3D deep vision platform approach has the promise to tackle many diseases.

“We have developed the capability to consider the full richness of medical imaging along with any other patient data.

"Our platform and AI approach will facilitate rapid decision support development, clinical discovery and propel MedyMatch into adjacent decision support opportunities."

MedyMatch's technology can be deployed suited to the customer’s requirement such as either a cloud or on-premises based solution, with minimised foot-print and seamless integration into a hospital enterprise, integrating smoothly into clinical workflow.

It will enable the physicians to accurately assess radiology images.

MedyMatch chief technical officer Dr Jacob Cohen said: "Consideration of the whole patient differentiates MedyMatch from traditional CAD applications.

"While traditional CADs strictly focus on pixel data, MedyMatch's technology applies deep learning and computer vision (Deep Vision) to interpret the full richness of the 3D imaging data together with the patient's Electronic Medical Record (EMR), allowing the system to consider the whole patient."