To train the model the researchers used two data sets of breast scans from the UK and the US. The UK dataset included scans from 25,856 women, while the US set contained mammograms from 3,097 women.
The new model was then pitted against six human radiologists, and outperformed them all on average by 11.5%. Mitchell said screening was a process that helps diagnose breast cancer at an early stage, when treatment is more likely to be successful. But it also has issues such as false positives. AI, she said, could help improve the screening process and take pressure of the UK's national health service.
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