AI in Breast Cancer Screenings

The use of artificial intelligence in radiology and imaging holds a lot of promise for patients and providers. One area in which AI could be especially helpful is in breast cancer screenings.

It’s common for breast cancer screenings to detect noncancerous lesions, which can lead to biopsies and surgeries that are ultimately unnecessary. But currently, there is no way to test if lesions found during breast cancer screenings are noncancerous or if they may become cancerous in the future without a biopsy.

However, that might be about to change. Researchers at the Massachusetts Institute of Technology’s (MIT) Computer Science and Artificial IntelligenceLaboratory (CSAIL), Massachusetts General Hospital, and Harvard Medical School designed an AI program that helped predict which findings on breast cancer screenings may become cancerous by the time providers would perform surgery. The program read 335 tests with 97% accuracy as to which would become cancerous. This helped reduce the number of breast biopsies for lesions that would not become cancerous.

Improving Accuracy

Another study found that a similar AI program, developed by researchers at Radboud University Medical Center in the Netherlands, was able to detect breast cancer in screening images with roughly the same amount of accuracy as radiologists. The program read more than 1,400 mammograms and was able to detect which readings were malignant, benign. Scientists believe that this AI program could be used to double-check radiologists to ensure an accurate diagnosis in their patients.

An additional AI program from researchers at Weill Cornell Medicine and New York-Presbyterian can determine whether or not cancer is present and also identify the types of cancer cells with almost 100% accuracy.

The Use of AI in the Future

While more research is needed, the use of AI programs shows the benefits they could bring to breast cancer screenings. In the coming years, radiologists and other providers may be able to use AI to help them make diagnostic and treatment decisions, providing their patients with advanced, high-quality care.

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