Mammography

For women with intermediate risk and a personal history of breast cancer, an emerging AI system offered an 81 percent AUC for breast cancer detection, according to new research.

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In sequential breast cancer screening with digital breast tomosynthesis (DBT), true positive examinations had more than double the AI case score of true negative examinations and the highest positive AI score changes from previous exams, according to new research.

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In a study of over 463,000 women who had screening mammography exams, adjunctive AI led to a 17.6 percent higher detection rate for breast cancer and a three percent increase in positive predictive value for recalls.

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New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.

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Originally cleared by the FDA in 2021, the SmartMammo Dx software for digital breast tomosynthesis (DBT) can now be utilized with the Senographe Pristina mammography systems from GE HealthCare.

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The new mammography system reportedly offers features that promote workflow efficiency as well as patient comfort.

As recommendations have become a commonplace expectation on radiology reports, is there a point where we are crossing the line?

Employing advanced deep learning convolutional neural networks, ProFound Detection Version 4.0 reportedly offers a 50 percent improvement in detecting cancer in dense breasts in comparison to the previous version of the software.

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In a 10-year study involving over 5,400 women with nearly 85 percent having dense breasts, contrast-enhanced mammography (CEM) demonstrated a 95.9 percent sensitivity rate for breast cancer.