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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

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

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

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

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

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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