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Using a standardized assessment, researchers in the U.K. compared the performance of a commercially available artificial intelligence (AI) algorithm with human readers of screening mammograms. Results of their findings were published in Radiology, a journal of the Radiological Society of North America (RSNA).
Mammographic screening does not detect every breast cancer. False-positive interpretations can result in women without cancer undergoing unnecessary imaging and biopsy. To improve the sensitivity and specificity of screening mammography, one solution is to have two readers interpret every mammogram.
According to the researchers, double reading increases cancer detection rates by 6% to 15% and keeps recall rates low. However, this strategy is labor-intensive and difficult to achieve during reader shortages.
“There is a lot of pressure to deploy AI quickly to solve these problems, but we need to get it right to protect women’s health,” says Yan Chen, PhD, professor of digital screening at the U.K.-based University of...