Can using AI risk prediction in breast cancer screening improve early detection?
Can using AI risk prediction in breast cancer screening improve early detection?
Publish Date: 2026-02-26 00:13:00
Source Domain: www.umassmed.edu
AI models can detect imaging features too subtle for the human eye, drawing on patterns learned from large datasets.
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Artificial intelligence is transforming medicine, but what does that mean for breast cancer screening? Researchers at UMass Chan Medical School are exploring how an AI-based tool might help identify women at higher risk for breast cancer and in doing so, detect cancers that standard mammograms might miss.
According to the American Cancer Society, breast cancer remains one of the most common cancers among women in the United States, and early detection is key to improving outcomes. Mammography, the current standard screening test, saves lives but has limitations, especially for women with dense breast tissue, where tumors can be harder to see.
Mohammed Salman Shazeeb, PhD, associate professor of radiology, and Gopal Vijayaraghavan, MD, MPH, professor of radiology, are part of a team testing an AI-driven risk assessment model developed in collaboration with investigators at the Massachusetts Institute of Technology. Supported by grants from state agencies and the Breast Cancer Research Foundation, the tool analyzes routine screening mammograms and assigns a risk score that estimates a woman’s likelihood of developing breast cancer in the next few years.
A targeted approach to supplemental screening
Instead of recommending supplemental imaging for every patient, the AI risk score helps the study team identify a smaller cohort of women who may benefit most from additional testing.
“Among the roughly 6 to 7 percent of women who scored above our risk threshold, we invited them for contrast-enhanced breast MRI,” said Dr. Shazeeb. “What’s striking is that all had normal screening mammograms, yet MRI found cancers in some of them that we would otherwise have missed.”
In the first 145 study participants, four additional cancers were identified through MRI despite negative mammography results—a yield that is…
