Zebra Medical Vision, the machine and deep learning company that is creating the next generation services for the healthcare industry. In the past two years Zebra-Med launched different algorithms on a monthly basis to better diagnose breast cancer, heart attacks, and other life-threatening diseases, and now the company is officially releasing the first ever algorithm to detect brain bleeds. This algorithm has just been granted CE approval.
The timely detection of brain bleeds is critical to a patient’s chances of healing. Research has shown that such bleeds are missed anywhere between 12% and 51% of the time, and nearly 6 million people die every year due to brain bleed related conditions. Such wide variability results in significantly reduced quality of patient care.
Zebra-Med’s new algorithm can identify such bleeds and provide a safety net for physicians in acute care settings. This new addition will be included in Zebra-Med’s growing Deep Learning Imaging Analytics platform. The algorithm, capable of detecting Intracranial Hemorrhages – or brain bleeds of different kinds, is now a part of a full suite of automated tools that was announced as Zebra-Meds’ AI1, which offers customers to pay a flat $1 per scan and get an unlimited number of AI algorithms.
The company plans to deploy the algorithm for point of care detection and for worklist prioritization helping physicians identify bleeds more accurately and with minimal delay. The algorithm broadens Zebra-Med’s AI1 “All-In-One” Imaging Analytics package, which has already analyzed more than 1M scans in over 5 countries.
“We’re excited to announce our first acute care algorithm with the potential to help radiologists better manage their workload, and properly prioritize urgent cases over others,” added Elad Benjamin, Co-Founder and CEO of Zebra Medical Vision in a statement. “This helps take PACS & Worklist management systems to the next level in helping radiologists manage patient care, all in a transparent and globally affordable business model. Over the next few months we plan to release several higher impact algorithms, on our path to provide a versatile AI based automated radiology assistant.”