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Evaluation of the performance of artificial intelligence (AI) after one year of use in breast cancer screening practice: is the promise being delivered?

Conclusion: Using Transpara concurrently in clinical practice allows to stratify examinations according to probability of cancer. Transpara increases cancer detection

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Reduced workload for breast radiologists: results from a retrospective study using artificial intelligence in mammographic screening

Conclusion: We found in a retrospective analysis that Transpara as a replacement for a second radiologist in a double reading

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AI-based strategy to reduce the recall rate and consensus meeting workload of double reading in breast cancer screening with digital mammography: a retrospective evaluation

Conclusion: Not reading exams with Transpara score 1-6 can reduce radiologists’ RR and workload in screening at the cost of

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Implementing AI to predict interval cancers in a national screening program

Conclusion: Transpara has the potential to reduce the stable high rate of interval cancer in case it is applied as

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Using an AI system and breast density to quantify the short-term risk of interval cancer in screening: a large retrospective evaluation

Conclusion: Transpara findings combined with breast density significantly improves detection of interval cancers.

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Using AI with single reading in screening: a simulation of the impact on tumour characteristics of detected cancers

Conclusion: Transpara can replace a radiologist in a double reading screening program, resulting in similar tumor characteristics compared to double

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