Mammogram Algorithm Improves Detection of Breast Cancer, Company Reports

Mammogram Algorithm Improves Detection of Breast Cancer, Company Reports
A researcher at Zebra Medical Vision who lost his wife to breast cancer has created a new mammography algorithm that uses machine and deep learning to diagnose breast cancer (BC), with results that the company claims are superior to those achieved using current methods. Zebra’s mammography algorithm, developed with the aid of thousands of patient studies, aims to optimize BC screening by reducing both false positive results and false negative results. According to the company, this will lead to fewer unnecessary tests (a cost-savings measure) and lower stress for patients. Doctors advise women over age 45 to be screened for BC every two years. Of these screenings, about 10 percent will be sent for specialized evaluation due to suspicious findings. But most women who undergo biopsies are found not to have cancer, while among the roughly  5 in every 1,000 who do develop breast cancer, one case of cancer is usually missed. In aiming for more accurate results, the Zebra algorithm may both protect women from unnecessary and pos
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