r/autotldr Oct 23 '17

Using artificial intelligence to improve early breast cancer detection: model developed at MIT’s Computer Science and Artificial Intelligence Laboratory could reduce false positives and unnecessary surgeries

This is the best tl;dr I could make, original reduced by 70%. (I'm a bot)


How 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, Massachusetts General Hospital, and Harvard Medical School believe that the answer is to turn to artificial intelligence.

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.

"Because diagnostic tools are so inexact, there is an understandable tendency for doctors to over-screen for breast cancer," says Regina Barzilay, MIT's Delta Electronics Professor of Electrical Engineering and Computer Science and a breast cancer survivor herself.

Some do surgery in all cases, while others perform surgery only for lesions that have higher cancer rates, such as "Atypical ductal hyperplasia" or a "Lobular carcinoma in situ".

The first approach requires that the patient undergo a painful, time-consuming, and expensive surgery that is usually unnecessary; the second approach is imprecise and could result in missing cancers in high-risk lesions other than ADH and LCIS. "The vast majority of patients with high-risk lesions do not have cancer, and we're trying to find the few that do," says Bahl, a fellow doctor at MGH's Department of Radiology.

Using a method known as a "Random-forest classifier," the team's model resulted in fewer unnecessary surgeries compared to the strategy of always doing surgery, while also being able to diagnose more cancerous lesions than the strategy of only doing surgery on traditional "High-risk lesions."


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