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New Study Finds Age and Race Impact Artificial Intelligence (AI) Performance on Digital Mammograms

Imaging Technology

christine.book Tue, 05/21/2024 - 10:36 May 21, 2024 — According to a newly-published study of nearly 5,000 screening mammograms interpreted by an FDA-approved AI algorithm, patient characteristics such as race and age influenced false positive results. Duke Health , breast radiologist and assistant professor at Duke University in Durham, NC.

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AI's impact on false-positive mammograms, breast cancer screening performance

AuntMinnie

million mammograms were performed in the U.S. Although mammogram is the most widely used screening modality, a known problem is that 9.5% Starting with mammography images, the work is important for finding ways to alleviate the region's radiologist workforce shortage and staffing pressures, according to Imperial College London.

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Mammogram reads improve when arranged from low to high breast density

AuntMinnie

Screening mammography exams arranged from low to high breast density can boost radiologists' interpretation performance, suggest findings published on October 8 in Radiology. This idea stems from previous studies' findings that between 20% and 50% of interval and screen-detected breast cancers were visible on prior screening mammograms.

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Lunit AI Releases Successful Study Results on Breast Cancer Screening Deployment

Imaging Technology

The original ScreenTrustCAD trial (2021–2022), published in The Lancet Digital Health , was the first prospective interventional study to demonstrate that AI could match or even surpass traditional two-radiologist systems. Previously, the waiting time for a clinical mammogram was five to six weeks. traditional double reading) to 5.5

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Medical Imaging of Fredericksburg Ranked First Place in “Best of the Burg” 2019 Contest

Medical Imaging of Fredericksburg

Medical Imaging of Fredericksburg Ranked First Place in “Best of the Burg” 2019 Contest Medical Imaging of Fredericksburg (MIF) took first place in the 2019 “Best of the Burg” contest, earning the award for “Best Medical Imaging”.

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AI can be used to 'rule-out' breast cancer on mammography

AuntMinnie

A deep-learning algorithm can rule out the presence of breast cancer on screening mammograms, improving specificity and yielding significant workflow and downstream savings, according to research published April 10 in Radiology. dataset 1: 143,593 mammograms interpreted by 11 breast radiologists from 2008 to 2017 U.S.

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AI algorithm flags interval breast cancer cases

AuntMinnie

They acquired data from full-field digital mammography and DBT exams between 2010 and 2019. The radiologists had varying degrees of experience ranging from three to 24 years. She and her team reviewed and classified interval breast cancers to evaluate a commercially available AI model’s (Transpara 1.7.1) performance within U.S.

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