AI and polygenic scores improve breast cancer risk assessment

AI Summary

A new study by Kaiser Permanente demonstrates that combining mammographic AI risk scores with polygenic and clinical risk scores significantly improves the accuracy of breast cancer risk assessment in women, supporting better preventive care strategies.

A risk model that combines a mammographic artificial intelligence (AI) risk score with polygenic and clinical risk scores more accurately identifies women at high risk of developing breast cancer than clinical risk scores used alone, finds a new Kaiser Permanente study. The study, published in the Journal of the National Cancer Institute, is one of the largest and most diverse to evaluate the ability of three approaches—mammography AI, polygenic and clinical—to predict breast cancer risk.