SHEFAYIM, Israel--(BUSINESS WIRE)--Fourth paragraph, first sentence of release should read: Zebra-Med’s Mammography algorithm aims to change that dynamic, by providing a state of the art clinical decision support product at a previously unprecedented price point (instead of Zebra-Med’s Mammography algorithm aims to change that dynamic, by providing a state of the art malignancy detection product at a previously unprecedented price point).
The corrected release reads:
ZEBRA MEDICAL VISION ANNOUNCES CE APPROVAL OF ITS SEVENTH AI IMAGING ALGORITHM - MAMMOGRAPHY LESION DETECTION
The new algorithm expands Zebra-Med’s footprint into Oncology, with the most affordable Mammo lesion detection package in the market.
Zebra Medical Vision (http://zebra-med.com/) announces today the CE regulatory approval of its newest algorithm to be included in its growing Deep Learning Imaging Analytics platform. The algorithm, capable of detecting suspected malignant lesions in Mammography scans - is the latest addition to other automated tools announced in the past as part of it’s “All-In-One” AI1 business model, among them algorithms that automatically detect brain bleeds, vertebral fractures, coronary artery disease, osteoporosis and more.
According to the American Cancer Society, breast cancer makes up 25% of all new cancer diagnoses in women globally - with nearly 1.7 million women being diagnosed annually. Survival rates, though improving - vary worldwide. In countries with advanced care, the rate is 80 to 90 percent for those with a first-stage diagnosis, and 24 percent if diagnosis occurs at a later stage. In developing countries the mortality rate is much worse, in large part due to the lack of early diagnostic capabilities. This lends significant importance to screening programs, that have the ability to detect breast cancer in its early stages.
Existing software solutions, called Mammo CAD (computer aided-detection) have been marketed for a number of years - attempting to assist mammographers in identifying suspicious lesions in mammography scans. Unfortunately, the large number of false alarms, coupled with a price tag that has placed these products within reach of only wealthier healthcare economies, have not led to widespread adoption globally.
Zebra-Med’s Mammography algorithm aims to change that dynamic, by providing a state of the art clinical decision support product at a previously unprecedented price point. The first version to be released supports 2D Hologic devices, and Zebra Medical Vision expects to add support for additional vendors, as well as 3D support during the course of 2019. 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.
“Early detection of breast cancer is a crucial component of disease prevention,” says Dr. Michael Fishman, a breast imaging radiologist at Beth Israel Deaconess Medical Center in Boston, Massachusetts. “An accurate AI assistant can provide a significant boost to radiologists seeking to provide the best care for their patients by increasing detection and limiting false positives."
“We have taken great care to produce a high performance aid in the detection of suspected malignant lesions,” says Elad Benjamin, Co-Founder and CEO of Zebra Medical Vision. “Mammography tools have had a checkered past, and we plan to usher a new level of performance with this algorithm and its follow on versions.”
About Zebra Medical Vision
Zebra Medical Vision uses deep learning to create and provide next generation products and services to the healthcare industry. Its Imaging Analytics Platform allows healthcare institutions to identify patients at risk of disease, and offer improved, preventative treatment pathways to improve patient care. Headquartered in Kibbutz Shefayim Israel, the Company was founded in 2014 by Co-Founders Eyal Toledano, Eyal Gura, and Elad Benjamin and funded by Khosla Ventures, Marc Benioff, Intermountain Investment Fund, OurCrowd and Dolby Ventures. For more information visit www.zebra-med.com.