AI challenge models can independently interpret mammograms

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while maintaining low recall rates, according to a study published in Radiology.

The RSNA Screening Mammography Breast Cancer Detection AI Challenge was a crowdsourced competition that took place in 2023, with more than 1,500 teams participating. The Radiology article details an analysis of the algorithms’ performance, led by Yan Chen, Ph.D., a professor of cancer screening at the University of Nottingham in the United Kingdom.

“We were overwhelmed by the volume of contestants and the number of AI algorithms that were submitted as part of the Challenge,” Prof. Chen said.

“It’s one of the most participated-in RSNA AI Challenges. We were also impressed by the performance of the algorithms given the relatively short window allowed for algorithm development and the requirement to source training data from open-sourced locations.”

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