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posted by Fnord666 on Friday October 20 2017, @07:54AM   Printer-friendly
from the I'm-sensing-a-theme dept.

Submitted via IRC for TheMightyBuzzard

Model developed at MIT's Computer Science and Artificial Intelligence Laboratory could reduce false positives and unnecessary surgeries.

Every year 40,000 women die from breast cancer in the U.S. alone. When cancers are found early, they can often be cured. Mammograms are the best test available, but they're still imperfect and often result in false positive results that can lead to unnecessary biopsies and surgeries.

One common cause of false positives are so-called "high-risk" lesions that appear suspicious on mammograms and have abnormal cells when tested by needle biopsy. In this case, the patient typically undergoes surgery to have the lesion removed; however, the lesions turn out to be benign at surgery 90 percent of the time. This means that every year thousands of women go through painful, expensive, scar-inducing surgeries that weren't even necessary.

How, then, can unnecessary surgeries be eliminated while still maintaining the important role of mammography in cancer detection? Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts General Hospital, and Harvard Medical School believe that the answer is to turn to artificial intelligence (AI).

As a first project to apply AI to improving detection and diagnosis, the teams collaborated to develop an AI system that uses machine learning to predict if a high-risk lesion identified on needle biopsy after a mammogram will upgrade to cancer at surgery.

Source: http://news.mit.edu/2017/artificial-intelligence-early-breast-cancer-detection-1017


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  • (Score: 0) by Anonymous Coward on Friday October 20 2017, @11:32AM

    by Anonymous Coward on Friday October 20 2017, @11:32AM (#585180)

    One of the interviewees expresses the hope that "machine learning [can be] a way to identify patterns and trends that are otherwise invisible to humans." Our perception has limitations; there's nothing magical in building a machine with different limitations. X-rays are not magic; radio telescopes are not magic; electron microscopes are not magic; infrared cameras are not magic.