Zebra Medical Vision Announces New Algorithm For Better Diagnosis of Breast Cancer

In In The News by Barbara Jacoby

Shefayim, Israel – October 2016 Zebra Medical Vision, a leading deep learning imaging analytics company, is announcing a new software algorithm for detecting breast cancer. The algorithm provides superior results compared to current tools, reducing misdiagnosis and false alarms. The researcher behind the algorithm, Phil Teare, lost his wife to cancer at an early age, and taught himself machine learning so he could recruit machines to the battle against the disease.

Women over 45 are advised to have a screening mammogram every two years. Approximately 10% of tests are sent for further evaluation due to suspicious findings, and approximately 5 women out of every 1,000 will develop breast cancer. Unfortunately, one of those 5 will be missed, and discovered too late. Furthermore, most women that are sent for biopsy follow ups turn out to be healthy – subjecting them to unnecessary tests and mental anguish. Zebra’s new algorithm  helps  provide better outcomes in two keys ways by reducing both false negatives and false positives. Less false negatives results in accurately detecting women with cancer, , and fewer  false positives means women will not have to  undergo unnecessary tests and stressful procedures.

Zebra Medical Vision developed their mammography algorithm using thousands of patient studies, and utilizing innovative deep learning techniques. Presenting the company’s results at the recent SIIM Conference on Machine Intelligence in Medical Imaging (CMIMI), Dr. Elnekave – Zebra’s Chief Medical Officer showcased algorithm results superior to those achieved by radiologists using current state of the art Computer Aided Detection methods for mammography.

“As a mammographer, I am cognizant of the vast variations in which breast cancer can manifest on a mammogram. Some of the most challenging cancer diagnoses are ones where the visual cues are not distinct lesions but rather regional asymmetry or architectural distortion in the breast tissue. I welcome Zebra Medical Vision’s algorithm that is a new generation of mammography analysis, which can help us in the mission of finding even the most subtle cancers as early as possible,” said Dr. Maya Cohen,  Director of the imaging Institute at Rabin Medical Center and Director of the Breast Health Center at Herzeliya Medical Center.

The mammography algorithm will be added to the company’s growing list of clinical algorithms which are part of an analytics engine that uses  machine and deep learning to to automatically read and diagnose medical imaging data. The Zebra engine has already yielded imaging insights that have been validated using hundreds of thousands of cases. Current algorithms are in the fields of bone health, cardiovascular analysis, liver and lung indications, and now mammography.

“We teach software to read and identify clinical conditions in imaging as part of our mission to help provide faster, more accurate radiology services at lower cost,” said Elad Benjamin, Zebra Medical Vision CEO. “We  machine and deep learning  to help diagnose  diseases responsible for the highest mortality rates,  and breast cancer is one of the top on that list. We believe that the tool we’re providing to radiologists, as well as new algorithms which we continuously release, will help them deal with the continuous pressure they face to increase output and maintain high quality of care.”

On track to create one hundred new insights in the next three years, Zebra has already secured partnerships with Dell Services and has received financial backing from Intermountain Healthcare, one of the leading healthcare organizations in the US. Zebra continues to expand its relationships and work with ACOs, HMOs and other payors and providers seeking to improve care at lower cost through the power of analytics, predictive modeling and preventative care.


From research to reality and commercialization, Zebra Medical Vision uses big data to deliver large scale clinical research platforms and next generation imaging analytics services to the healthcare industry. Its Imaging Analytics allow healthcare institutions to identify patients at risk of disease, and offer improved, preventative treatment pathways to improve patient care. The Zebra Research Platform provides researchers the largest structured clinical data set globally, and makes it available for research, including a complete development, hosting, storage and computing environment, and follow-on regulatory and commercialization services. Headquartered in Kibbutz Shefayim Israel, the Company was founded in 2014 by Co-Founders Eyal Toledano, Eyal Gura, and Elad Benjamin and funded by OurCrowd, Marc Benioff, Khosla Ventures, and the Intermountain Healthcare innovation fund. For more information visit www.zebra-med.com.