Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds.

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Exploring the prediction performance for breast cancer risk based on volumetric mammographic density at different thresholds.

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2018 nî lūn-bûn

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2018年の論文

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年學術文章

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2018年學術文章

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Exploring the prediction perfo ...... nsity at different thresholds.

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Exploring the prediction perfo ...... nsity at different thresholds.

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Exploring the prediction perfo ...... nsity at different thresholds.

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Exploring the prediction perfo ...... nsity at different thresholds.

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Exploring the prediction perfo ...... nsity at different thresholds.

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Exploring the prediction perfo ...... nsity at different thresholds.

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P1476

Exploring the prediction perfo ...... ensity at different thresholds

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P2093

D Gareth Evans

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Elaine F Harkness

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Jack Cuzick

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Susan Astley

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P2860

Stromal characteristics may hold the key to mammographic density: the evidence to date

Digital mammographic density and breast cancer risk: a case-control study of six alternative density assessment methods

Mammographic density defined by higher than conventional brightness threshold better predicts breast cancer risk for full-field digital mammograms.

Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort

Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations

Comparison of Clinical and Automated Breast Density Measurements: Implications for Risk Prediction and Supplemental Screening

AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes.

Clinical and epidemiological issues in mammographic density.

Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS.

A first evaluation of breast radiological density assessment by QUANTRA software as compared to visual classification.

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s13058-018-0979-x

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scholarly article

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10.1186/S13058-018-0979-X

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Adam R Brentnall

Chao Wang

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2018-06-08T00:00:00Z

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1104481205

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29884207

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