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Comparing the value of mammographic features and genetic variants in breast cancer risk prediction
Yirong Wu
, Jie Liu
, David Page
, Peggy Peissig
,
Catherine McCarty
, Adedayo A. Onitilo
, Elizabeth S. Burnside
Administration (DMED)
Research output
:
Contribution to journal
›
Article
›
peer-review
8
Scopus citations
Overview
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Keyphrases
Genetic Variants
100%
Breast Cancer Risk Assessment
100%
Mammographic Features
100%
Mammographic Findings
37%
Risk Factors
12%
Breast
12%
Risk Prediction
12%
Personalized Medicine
12%
Breast Cancer Risk
12%
Information Theory
12%
Mutual Information
12%
Retrospective Case-Control Design
12%
Low Penetrance
12%
Area under the ROC Curve
12%
Bayesian Network
12%
Bayesian Information
12%
Discriminative Ability
12%
Bayesian Reasoning
12%
Medicine and Dentistry
Breast Cancer
100%
Cancer Risk
100%
Personalized Medicine
25%
Genetic Variability
25%
Case-Control Study
25%
Penetrance
25%