Are better AI algorithms for breast cancer detection also better at predicting risk? A paired case-control study.

ABSTRACT:

Background

There is increasing evidence that artificial intelligence (AI) breast cancer risk evaluation tools using digital mammograms are highly informative for 1-6 years following a negative screening examination. We hypothesized that algorithms that have previously been shown to work well for cancer detection will also work well for risk assessment and that performance of algorithms for detection and risk assessment is correlated.

Methods

To evaluate our hypothesis, we designed a case-control study using paired mammograms at diagnosis and at the previous screening visit. The study included n = 3386 women from the OPTIMAM registry, that includes mammograms from women diagnosed with breast cancer in the English breast screening program 2010-2019. Cases were diagnosed with i

SUBMITTER: Santeramo R 

PROVIDER: S-EPMC10848404 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature