Elizabeth Burnside M.D., MPH, M.S.
Elizabeth Burnside M.D., MPH, M.S.
Professor of Radiology, University of Wisconsin School of Medicine and Public Health
Verified email at uwhealth.org - Homepage
Cited by
Cited by
ACR BI-RADS atlas: breast imaging reporting and data system; mammography, ultrasound, magnetic resonance imaging, follow-up and outcome monitoring, data dictionary
American College of Radiology, CJ D'Orsi
ACR, American College of Radiology, 2013
Introduction to statistical relational learning
D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ...
MIT press, 2007
Acr bi-radsŪ mammography
EA Sickles, CJ d’Orsi, LW Bassett, CM Appleton, WA Berg, ES Burnside
ACR BI-RADSŪ atlas, breast imaging reporting and data system 5, 2013, 2013
Differentiating Benign from Malignant Solid Breast Masses with US Strain Imaging
ES Burnside, TJ Hall, AM Sommer, GK Hesley, GA Sisney, WE Svensson, ...
Radiology 245 (2), 401-410, 2007
MR imaging radiomics signatures for predicting the risk of breast cancer recurrence as given by research versions of MammaPrint, Oncotype DX, and PAM50 gene assays
H Li, Y Zhu, ES Burnside, K Drukker, KA Hoadley, C Fan, SD Conzen, ...
Radiology 281 (2), 382-391, 2016
The ACR BI-RADSŪ experience: learning from history
ES Burnside, EA Sickles, LW Bassett, DL Rubin, CH Lee, DM Ikeda, ...
Journal of the American College of Radiology 6 (12), 851-860, 2009
Use of Microcalcification Descriptors in BI-RADS 4th Edition to Stratify Risk of Malignancy
ES Burnside, JE Ochsner, KJ Fowler, JP Fine, LR Salkowski, DL Rubin, ...
Radiology 242 (2), 388-395, 2007
Toward Best Practices in Radiology Reporting
CE Kahn Jr, CP Langlotz, ES Burnside, JA Carrino, DS Channin, ...
Radiology 252 (3), 852-856, 2009
Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set
H Li, Y Zhu, ES Burnside, E Huang, K Drukker, KA Hoadley, C Fan, ...
NPJ breast cancer 2 (1), 1-10, 2016
Comparison of Logistic Regression and Artificial Neural Network Models in Breast Cancer Risk Estimation
T Ayer, J Chhatwal, O Alagoz, CE Kahn Jr, RW Woods, ES Burnside
Radiographics 30 (1), 13-22, 2010
Patient, faculty, and self-assessment of radiology resident performance: A 360-degree method of measuring professionalism and interpersonal/communication skills
J Wood, J Collins, ES Burnside, MA Albanese, PA Propeck, F Kelcz, ...
Academic radiology 11 (8), 931-939, 2004
Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration
T Ayer, O Alagoz, J Chhatwal, JW Shavlik, CE Kahn Jr, ES Burnside
Cancer 116 (14), 3310-3321, 2010
Effects of screening and systemic adjuvant therapy on ER-specific US breast cancer mortality
D Munoz, AM Near, NT Van Ravesteyn, SJ Lee, CB Schechter, O Alagoz, ...
JNCI: Journal of the National Cancer Institute 106 (11), 2014
Optimal breast biopsy decision-making based on mammographic features and demographic factors
J Chhatwal, O Alagoz, ES Burnside
Operations research 58 (6), 1577-1591, 2010
Prediction of clinical phenotypes in invasive breast carcinomas from the integration of radiomics and genomics data
W Guo, H Li, Y Zhu, L Lan, S Yang, K Drukker, EA Morris, ES Burnside, ...
Journal of medical imaging 2 (4), 041007, 2015
Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience
ES Burnside, DL Rubin, JP Fine, RD Shachter, GA Sisney, WK Leung
Radiology 240 (3), 666-673, 2006
A Bayesian network for mammography.
E Burnside, D Rubin, R Shachter
Proceedings of the AMIA Symposium, 106, 2000
Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings
ES Burnside, J Davis, J Chhatwal, O Alagoz, MJ Lindstrom, BM Geller, ...
Radiology 251 (3), 663-672, 2009
Circulating serum xenoestrogens and mammographic breast density
BL Sprague, A Trentham-Dietz, CJ Hedman, J Wang, JDC Hemming, ...
Breast Cancer Research 15 (3), 1-8, 2013
An integrated approach to learning Bayesian networks of rules
J Davis, E Burnside, I de Castro Dutra, D Page, VS Costa
European Conference on Machine Learning, 84-95, 2005
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