Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy

Elizabeth S. Burnside; Jie Liu; Yirong Wu; Adedayo A. Onitilo; Catherine A. McCarty; C. David Page; Peggy L. Peissig; Amy Trentham-Dietz; Terrie Kitchner; Jun Fan; Ming Yuan

doi:10.1016/j.acra.2015.09.007

Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy

Elizabeth S. Burnside
, Jie Liu
, Yirong Wu
, Adedayo A. Onitilo
, Catherine A. McCarty
, C. David Page
, Peggy L. Peissig
, Amy Trentham-Dietz
, Terrie Kitchner
, Jun Fan
, Ming Yuan

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

14 Citations (Scopus)

Original language	English
Pages (from-to)	62-69
Number of pages	8
Journal	Academic Radiology
Volume	23
Issue number	1
DOIs	https://doi.org/10.1016/j.acra.2015.09.007
Publication status	Published - Jan 2016

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1016/j.acra.2015.09.007

Cite this

Burnside, E. S., Liu, J., Wu, Y., Onitilo, A. A., McCarty, C. A., Page, C. D., Peissig, P. L., Trentham-Dietz, A., Kitchner, T., Fan, J., & Yuan, M. (2016). Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy. Academic Radiology, 23(1), 62-69. https://doi.org/10.1016/j.acra.2015.09.007

@article{9059bd3847fe424aaf657328fdde8200,

title = "Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy",

author = "Burnside, \{Elizabeth S.\} and Jie Liu and Yirong Wu and Onitilo, \{Adedayo A.\} and McCarty, \{Catherine A.\} and Page, \{C. David\} and Peissig, \{Peggy L.\} and Amy Trentham-Dietz and Terrie Kitchner and Jun Fan and Ming Yuan",

note = "The authors acknowledge the support of the Wisconsin Genomics Initiative from the state of Wisconsin and support from the National Institutes of Health (grants: R01CA127379, R01CA127379-03S1, R01GM097618, R01LM011028, R01ES017400). We also acknowledge support from the eMERGE Network (U01HG004608), the UW Institute for Clinical and Translational Research (UL1TR000427) and the UW Carbone Comprehensive Cancer Center (P30CA014520).",

year = "2016",

month = jan,

doi = "10.1016/j.acra.2015.09.007",

language = "English",

volume = "23",

pages = "62--69",

journal = "Academic Radiology",

issn = "1076-6332",

publisher = "Elsevier Inc.",

number = "1",

}

TY - JOUR

T1 - Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy

AU - Burnside, Elizabeth S.

AU - Liu, Jie

AU - Wu, Yirong

AU - Onitilo, Adedayo A.

AU - McCarty, Catherine A.

AU - Page, C. David

AU - Peissig, Peggy L.

AU - Trentham-Dietz, Amy

AU - Kitchner, Terrie

AU - Fan, Jun

AU - Yuan, Ming

N1 - The authors acknowledge the support of the Wisconsin Genomics Initiative from the state of Wisconsin and support from the National Institutes of Health (grants: R01CA127379, R01CA127379-03S1, R01GM097618, R01LM011028, R01ES017400). We also acknowledge support from the eMERGE Network (U01HG004608), the UW Institute for Clinical and Translational Research (UL1TR000427) and the UW Carbone Comprehensive Cancer Center (P30CA014520).

PY - 2016/1

Y1 - 2016/1

U2 - 10.1016/j.acra.2015.09.007

DO - 10.1016/j.acra.2015.09.007

M3 - Journal article

SN - 1076-6332

VL - 23

SP - 62

EP - 69

JO - Academic Radiology

JF - Academic Radiology

IS - 1

ER -