
AI can predict interval breast cancer risk up to three years after a negative mammogram.
Key Details
- 1A deep learning algorithm (Mirai) assessed three-year interval cancer risk using negative mammograms.
- 2Study evaluated over 134,000 patients across two U.K. sites.
- 3Algorithm predicted up to 43% of interval cancers before they developed.
- 4AI-generated risk scores could guide personalized screening and supplemental imaging.
- 5Interval cancers are typically more aggressive and have worse prognoses.
Why It Matters
Being able to predict interval cancers from seemingly normal mammograms can enable radiologists and clinicians to personalize screening intervals and deliver earlier, targeted interventions, especially in healthcare settings with longer screening intervals. This may lead to better outcomes for women at higher risk and more efficient use of imaging resources.

Source
Radiology Business
Related News

•AuntMinnie
Study: Computer Vision Models Best LLMs in Chest CT Breast Abnormality Detection
Computer vision models (CVMs) surpass large language models (LLMs) in accurately labeling incidental breast abnormalities on chest CT scans.

•AuntMinnie
Deep Learning Models Rival Radiologists for Pancreatic Cancer Detection on CT
Deep-learning models achieved comparable or superior accuracy to experienced radiologists in detecting pancreatic cancer on CT scans, especially for small tumors.

•Radiology Business
Radiology AI Devices at Elevated Risk for FDA Recalls, Study Finds
Radiology AI devices are more likely to face FDA recalls, largely due to deviations from intended use and incomplete clinical data.