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An AI-based Mammography Screening Protocol: Outcome and Radiologists Workload

Link to the article Background: Developments in artificial intelligence (AI) systems to assist radiologists in reading screening mammograms could improve

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Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program

Read the full publication Background: Artificial intelligence (AI) has shown promising results for cancer detection in mammographic screening. However, evidence

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Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms

https://pubs.rsna.org/doi/10.1148/radiol.210832  Background: Inclusion of mammographic breast density in breast cancer risk models improves accuracy, but accuracy remains modest. Interval cancer

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Artificial Intelligence as a support to the radiologists’ screen reading of mammograms – A retrospective study

AIM AND OBJECTIVE To explore the performance of an artificial intelligence (AI)-system on cancer detection in a population based screening

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Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance

Objectives This study evaluated the performance of Transpara to discriminate recalled benign from recalled malignant mammographic screening abnormalities, aiming to

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Impact of artificial intelligence decision support using deep learning on breast cancer screening interpretation with single-view wide-angle digital breast tomosynthesis

Radiology 2021 Objectives: The high data volume of digital breast tomosynthesis (DBT) and the lack of agreement regarding its implementation

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