Researchers from Memorial University of Newfoundland in St. John’s, Canada, used a decision tree and simulation model to assess the cost-effectiveness of eight different breast cancer screening strategies. They found that the most cost-effective approach relied on AI analysis of an index screening mammogram for risk stratification; women identified as low risk would not receive any additional screening in their 40s, while high-risk women would have annual screening mammograms.

“By accurately identifying and screening more high-risk women and avoiding screening for low-risk women, this…