AI rivals human radiologists at breast-cancer detection – Physics World - Medical Physics Web

A comparison of three commercially available artificial intelligence (AI) systems for breast cancer detection has found that the best of them performs as well as a human radiologist.

Researchers applied the algorithms to a database of mammograms captured during routine cancer screening of nearly 9000 women in Sweden.

“The motivation behind our study was curiosity about how good AI algorithms had become in relation to screening mammography,” says Fredrik Strand at Karolinska Institutet in Stockholm.

The sample included 739 women who had been diagnosed with breast cancer less than 12 months after screening, and 8066 women who had received no diagnosis of breast cancer within 24 months.

Also included in the dataset, but not accessible to the algorithms, were the binary “normal/abnormal” decisions made by the first and second human readers for each image.

Some of the abnormal cases identified by the algorithms were in patients whose images the human readers had classified as normal, but who then received a cancer diagnosis clinically (outside of the screening programme) less than a year after the examination.

Strand and colleagues showed that this was the case by measuring the performance of combinations of human and AI readers: pairing AI-1 with an average human first reader, for example, increased the number of cancers detected during screening by 8%.