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Study shows implementing the newly cleared software can slightly improve sensitivity and false negatives.
Adding artificial intelligence (AI) to mammography interpretation can help radiologists catch more cancers, according to a new study using a tool awarded U.S. Food & Drug Administration 510(k) clearance earlier this year.
Currently, the body of literature around the effectiveness of AI with mammography is small because the use of the tools is still in the early stage of investigation. In order to grow the body of knowledge, researchers from AI company Therapixel tested their software, MammoScreen™, to see if it could benefit providers. What they found is slightly improved sensitivity and a better false-negative rate.
“The present study confirms the observed trend that AI algorithms are able to improve radiologist’ success rate in breast cancer detection, supporting the conclusion that radiologists and AI achieve better performance together than each of them individually,” the Therapixel team said.
The team, led by Serena Pacilè, Ph.D., clinical research manager at Therapixel, published their results on Nov. 4 in Radiology: Artificial Intelligence.
Although mammography is considered the gold standard for breast imaging, between 30 percent and 40 percent of breast cancers go undetected on screenings, the team said, and only 10 percent of women called back for additional screening are ultimately found to have cancer. But, AI has been shown to provide better results.
“Preliminary investigations have demonstrated that the use of AI systems as concurrent readers for interpreting mammograms can improve efficiency of the radiologist in terms of time, sensitivity, and specificity,” the team said.
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