Artificial Intelligence Technologies for Breast Cancer Screening

B reast cancer is the most common type of cancer in women globally, occurring in about one in eight women, but early detection and treatment can considerably improve outcomes. Consequently, many developed nations have implemented large-scale mammography screening programs. Mammography has been the frontline screening tool for breast cancer for decades with more than 200 million women being examined each year around the globe. Despite its widespread use, the interpretation of mammograms is affected by high rates of false positives and false negatives. False positives can lead to patient anxiety, unnecessary follow-up, and invasive diagnostic procedures. In contrast, a false negative can result in delayed detection, advancement of the diseases, and being less amenable to treatment. For example, in the United States, approximately 10 percent of the 40 million women who undergo breast cancer screening each year are recalled for further diagnostic imaging, and only 4-5 percent of these women are ultimately diagnosed with breast cancer. This means that more than half a million would not have to undergo unnecessary diagnostic work-up.