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Using a convolutional neural network to predict readers' estimates of mammographic density for breast cancer risk assessment

机译：使用卷积神经网络预测读者对乳腺癌风险评估的乳房X光密度的估计

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Martin Fergie; Michael Berks; Elaine F. Harkness; Susan Astley; Johan Hulleman; Adam R. Brentnall; Jack Cuzick; Gareth Evans; Georgia V. Ionescu;
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1. Application of convolutional neural networks to breast biopsies to delineate tissue correlates of mammographic breast density [J] . Maeve Mullooly, Babak Ehteshami Bejnordi, Ruth M. Pfeiffer, NPJ breast cancer. . 2019,第1期

机译：卷积神经网络在乳房活组织检查中应用乳房X一种乳房X线乳房密度的相关性
2. uing Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model [J] . Jeffrey A. Tice Steven R. Cummings Rebecca Smith-Bindman Laura Ichikawa William E. Barlow and Karla Kerlikowske Annals of Internal Medicine . 2008,第5期

机译：利用临床因素和乳腺钼靶X线密度评估乳腺癌风险：开发和验证新的预测模型
3. Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model. [J] . Tice JA, Cummings SR, Smith-Bindman R, Annals of Internal Medicine . 2008,第5期

机译：使用临床因素和乳房X线摄影术的乳房密度来估计乳腺癌风险：开发和验证新的预测模型。
4. Using a Convolutional Neural Network to Predict Readers' Estimates of Mammographic Density for Breast Cancer Risk Assessment [C] . Georgia V. Ionescu, Martin Fergie, Michael Berks, International Workshop on Breast Imaging . 2018

机译：使用卷积神经网络预测读者对乳腺X线摄影密度的估计，以评估乳腺癌的风险
5. The relation between dietary and serum cholesterol and mammographic density as a risk factor for breast cancer [D] . Tamburrini, Ame-Lia 2008

机译：饮食和血清胆固醇与乳腺钼靶密度之间的关系是乳腺癌的危险因素
6. Prediction of reader estimates of mammographic density using convolutional neural networks [O] . Georgia V. Ionescu, Martin Fergie, Michael Berks, 2019

机译：使用卷积神经网络预测读者对乳腺X线密度的估计
7. Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model [O] . Karla Kerlikowske Md 2015

机译：利用临床因素和乳房乳房密度估计乳腺癌风险：一种新的预测模型的开发和验证

Using a convolutional neural network to predict readers' estimates of mammographic density for breast cancer risk assessment

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