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MIT's oncological risk AI calculates cancer chances regardless of race
Artificial intelligence and machine learning systems continue to be adopted into an ever wider array of healthcare applications, such as assisting doctors with medical image diagnostics. Capable of understanding X-rays and rapidly generating MRIs -- sometimes even able to spot cases of COVID -- these systems have also proven effective at noticing early signs of breast cancer which might otherwise be missed by radiologists. Google and IBM, as well as medical centers and university research teams around the world, have all sought to develop such cancer-catching algorithms.
MIT's AI can identify breast cancer risk as reliably as a radiologist
Breast cancer affects one in eight women in the US. There are multiple factors involved in developing the disease, but one issue is dense breast tissue. Some 40 percent of US women have dense breast tissue, which alone increases the risk of breast cancer, and can make mammogram screening more difficult. Now, researchers from MIT and Massachusetts General Hospital (MGH) have developed an automated model that assesses dense breast tissue in mammograms as reliably as expert radiologists.
