
Certain breast cancer types, like luminal cancer and those in dense breasts, are more likely to be missed by AI in mammography screening.
Key Details
- 1South Korean researchers reviewed breast images from nearly 1,100 women screened between 2014 and 2020.
- 2AI tools were found to miss cancers with features such as luminal subtype, dense breast tissue, and lesions outside the mammary zone.
- 3The study was published in RSNA's journal Radiology.
- 4Experts urge careful assessment of cases at higher risk of AI error.
Why It Matters
Understanding which cancers AI is most likely to miss can help optimize AI integration into breast imaging workflows, ensuring that radiologists remain vigilant in specific high-risk contexts. This research offers guidance to improve both detection and patient outcomes.

Source
Radiology Business
Related News

•Radiology Business
GE HealthCare and RadNet Expand Global AI Mammography Partnership
GE HealthCare and RadNet are extending their partnership globally to offer AI-enhanced mammography systems.

•AuntMinnie
Radiology Receives Declining Share of Industry Research Funding
Radiologists received only 1.1% of industry-funded research payments in 2024, with a continuing downward trend.

•AuntMinnie
GPT-4o AI Matches Radiologists in Follow-Up Imaging Recommendations
GPT-4o matched the performance of experienced radiologists and surpassed residents in recommending follow-up imaging from routine radiology reports.