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Frequency and characteristics of errors by artificial intelligence (AI) in reading screening mammography: a systematic review
- Truvace record
- TRV-2026-2725raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
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PURPOSE: Artificial intelligence (AI) for reading breast screening mammograms could potentially replace (some) human-reading and improve screening effectiveness. This systematic review aims to identify and quantify the types of AI errors to better understand the consequences of implementing this technology. METHODS: Electronic databases were searched for external validation studies of the accuracy of AI algorithms in real-world screening mammograms. Descriptive synthesis was performed on error types and frequenc…
The problem
In a systematic review of seven studies covering 447,676 screening mammograms, the pooled false positive rate of the Transpara AI tool was 71.83% at threshold 3 and still 10.77% at threshold 9, and raising the threshold pushed missed cancers up to 0.12%.
Sources
1 on file- Breast Cancer Research and Treatmentdoi:10.1007/s10549-024-07353-3
What the review found when it combined the studies
These are the review’s own pooled results, copied from its abstract. Truvace did not recalculate them.
False negative proportion of AI reading screening mammograms at Transpara threshold 9
Proportion 0.12% (95% CI 0.06% to 0.26%)
The review’s own words
The pooled FNP increased incrementally from 0.02% [95% CI 0.01, 0.03] at Transpara 3 to 0.12% [95% CI 0.06, 0.26] (Transpara 9), consistent with a trade-off with FPP.
False positive proportion of AI reading screening mammograms at Transpara threshold 3
Proportion 71.83% (95% CI 69.67% to 73.90%)
The review’s own words
Pooled FPP decreased incrementally with increasing Transpara threshold (71.83% [95% CI 69.67, 73.90] at Transpara 3 to 10.77% [95% CI 8.34, 13.79] at Transpara 9).
False positive proportion of AI reading screening mammograms at Transpara threshold 9
Proportion 10.77% (95% CI 8.34% to 13.79%)
The review’s own words
Pooled FPP decreased incrementally with increasing Transpara threshold (71.83% [95% CI 69.67, 73.90] at Transpara 3 to 10.77% [95% CI 8.34, 13.79] at Transpara 9).
False negative proportion of AI reading screening mammograms at Transpara threshold 3
Proportion 0.02% (95% CI 0.01% to 0.03%)
The review’s own words
The pooled FNP increased incrementally from 0.02% [95% CI 0.01, 0.03] at Transpara 3 to 0.12% [95% CI 0.06, 0.26] (Transpara 9), consistent with a trade-off with FPP.
False positive proportion of AI reading screening mammograms at Transpara threshold 5
Proportion 46.86% (95% CI 39.33% to 54.53%)
The review’s own words
The most commonly reported prospective triage thresholds were Transpara 5 (pooled FPP 46.86% [95% CI 39.33, 54.53])
Code checks every number above against the review’s text before it is shown. The short labels are an AI model’s reading of that text, so the review’s own sentence sits under each one. A pooled figure is only as strong as the studies behind it. How Truvace uses pooled results
Cite this record
v1Truvace Impact Record TRV-2026-2725, v1: “Frequency and characteristics of errors by artificial intelligence (AI) in reading screening mammography: a systematic review.” Truvace, 2026-11-12. /record/TRV-2026-2725 (accessed on the day you copy it). sha256 6163ae17aaaaf95c…
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