Zebra Medical Vision, an Israeli digital healthcare startup,
claims to have developed an algorithm that has the potential to
improve breast cancer detection.
Founded in 2014 and backed by the likes of Salesforce billionaire
Marc Benioff with $20 million (£16 million), the Tel Aviv-based
company says it has taught an algorithm to identify early signs
of breast cancer with the help of thousands of previous
That constantly improving algorithm — trained using a technique
known as machine learning, which is a type of AI that
equips computers with the ability to learn without being
explicitly programmed — is now better than radiologists
using the best Computer Aided Detection (CAD) methods for
mammography, the company claims.
Eldad Elnekave, Zebra’s chief medical officer, told Business
Insider in Tel Aviv that the algorithm can detect half of the
breast cancer cases that are currently being missed by
radiologists. Radiologists working for the NHS fail to spot
breast cancer in thousands of mammograms every year, according to The Telegraph. The condition
affects one in eight women in their lifetime, according to UK charity Breast Cancer Care.
“The challenge here is there’s so much background noise in
breasts,” said Elnekave. “Breasts can be dense, they can be not
dense, they can be have implants, and so on. There are so many
possibilities so to find the actual breast cancer is a challenge.
This is where we could utilise the fact that we had an enormous
database of mammograms. We have 344,000 breast cancer studies
The mammography algorithm will be added to the company’s growing
list of clinical
algorithms, which can automatically read and
diagnose medical imaging data. Current algorithms are in the
fields of bone health, cardiovascular analysis, liver and lung
indications, and now mammography.
Dr Maya Cohen, director of the imaging Institute at Rabin Medical
Center and director of the Breast Health Center at Herzeliya
Medical Center in Israel, endorsed Zebra’s technology in a
press release published by the company.
“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,” she
said in a statement, adding that Zebra’s algorithm could
help mammographers detect even the “most subtle” cancers.
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