Breast cancer is the second leading cancer-related cause of death among women in the U.S. It’s estimated that in 2015, 232,000 women were diagnosed with the disease and approximately 40,000 died from it. And while exams like mammography have come into wide practice — in 2014, over 39 million breast cancer screenings were performed in the U.S. alone — they’re not always reliable. About 10% to 15% of women who undergo a mammogram are asked to return following an inconclusive analysis.
Fortunately, with the help of AI, scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital are making steps toward more consistent and reliable screening procedures. In a newly published paper in the journal Radiology, they describe a machine learning model that can predict from a mammogram if a patient is likely to develop breast cancer as many as five years in the future.