Ultrasound 2016

Dec 6th, 2016Dec 8th, 2016
York, --
GB
https://www.bmus.org
The 48th annual scientific meeting of the British Medical Ultrasound Society.
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C-index for Cox regression and random survival forests models using two feature sets. Adding historical registry data decreases the C-index for Cox regression but increased it for the random survival forests model, consistent with the non-linear structure in the registry data.
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Screening mammograms and AI score changes are depicted over time in two individuals with screen-detected cancer. Full-field digital mammograms show craniocaudal (top) and mediolateral (bottom) views of the left and right breast. The description below each mammogram indicates whether AI scores from three AI-based computer-aided detection systems (AI-1, AI-2, and AI-3) were above or below the 90th percentile. (A) Mammograms from three screening time points (in 2009, 2011, and 2014) in an individual who was diagnosed in February 2014 (at age 73 years) with a left-sided 25-mm grade 2 invasive breast carcinoma, no special type (arrow). Mammographic breast density was classified as BI-RADS B on all three mammograms. (B) Mammograms from four screening time points (in 2009, 2011, 2013, and 2015) in an individual who was diagnosed in October 2015 (at age 65 years) with a left-sided 45-mm grade 2 lobular carcinoma (arrow). Mammographic breast density was classified as BI-RADS C on all four mammograms. Screen-detected cancers were defined as those diagnosed within 90 days for individuals who were recalled at screening (*).
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