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Using Artificial Intelligence to Improve Early Breast Cancer Detection


From left, Manisha Bahl, director of the Massachusetts General Hospital Breast Imaging Fellowship Program; MIT professor Regina Barzilay, and Constance Lehman, professor at Harvard Medical School.

Researchers at the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory, Massachusetts General Hospital, and Harvard Medical School believe artificial intelligence can eliminate unnecessary breast cancer surgeries while maintaining the important role of mammography in cancer detection.

Credit: Jason Dorfman/CSAIL

Researchers at the Massachusetts Institute of Technology's (MIT) Computer Science and Artificial Intelligence Laboratory (CSAIL) are working on the first project to apply artificial intelligence (AI) to improving the detection and diagnosis of breast cancer.

The researchers developed an AI system that uses machine learning to predict if a high-risk lesion identified by a needle biopsy after a mammogram will upgrade to cancer at surgery.

The researchers tested the system on 335 high-risk lesions, correctly diagnosing 97% of the breast cancers as malignant and reducing the number of benign surgeries by more than 30% compared to existing approaches.

The machine-learning model was trained on more than 600 existing high-risk lesions, and now is able to look for patterns among many different data elements such as demographics, family history, past biopsies, and pathology reports. The model uses a method known as a "random-forest classifier," which results in fewer unnecessary surgeries.

From MIT News
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