Elizabeth S. Burnside, MD, MPH, MS Print Friendly PageFaculty, University of Wisconsin School of Medicine and Public Health
In medical school, Dr. Burnside got her MD degree combined with master’s in Public Health. In addition, between residency and fellowship, Dr. Burnside got a master’s degree in Medical Informatics from Stanford University. As a result her research has involved the use of artificial intelligence methods to improve decision-making in the domain of breast imaging. This multidisciplinary research is facilitated by affiliate appointments in the Departments of Biostatistics and Medical Informatics and Population Health Science at UW. Dr. Burnside received the General Electric Radiology Research Fellowship from 2003-2005 to investigate the utility of a probabilistic computer model to improve decision-making in mammography. She has published 23 peer review articles and has served on an NIH Study Section (DMG). Dr. Burnside is a subspecialty trained breast imager and provides all imaging procedures for the early diagnosis of breast cancer. She was recently elected a Fellow in the Society of Breast Imaging and is a member of the The American College of Radiology Comission on Breast Imaging Education. Dr. Burnside is a member of the UW Health Breast Center.
UW Health Clinics
UW School of Medicine and Public Health
|Department of Radiology|
Professional Certifications and Education
University of California San Francisco, San Francisco, CA, CA
University of California San Francisco, San Francisco, CA, CA
Tufts University School of Medicine, Boston, MA, 1993
|Medical interpreters are available to help patients communicate with hospital and clinic staff. For more information, please contact interpreter services at (608) 262-9000.|
Our doctors provide a wide range of services. The following list represents some, but not all, of the procedures offered by this physician.
Liu J Zhang C Burnside E Page D .
Multiple Testing under Dependence via Semiparametric Graphical Models. Proc Int Conf Mach Learn. 2014 Dec 31;2014:955-963
[PubMed ID: 25309970]
Munoz D Near AM van Ravesteyn NT Lee SJ Schechter CB Alagoz O Berry DA Burnside ES Chang Y Chisholm G de Koning HJ Ali Ergun M Heijnsdijk EA Huang H Stout NK Sprague BL Trentham-Dietz A Mandelblatt JS Plevritis SK .
Effects of screening and systemic adjuvant therapy on ER-specific US breast cancer mortality. J Natl Cancer Inst. 2014 Nov;106(11)
[PubMed ID: 25255803]
Obadina ET Dubenske LL McDowell HE Atwood AK Mayer DK Woods RW Gustafson DH Burnside ES .
Online support: Impact on anxiety in women who experience an abnormal screening mammogram. Breast. 2014 Sep 2;
[PubMed ID: 25193424]
Ayvaci MU Alagoz O Chhatwal J Munoz del Rio A Sickles EA Nassif H Kerlikowske K Burnside ES .
Predicting invasive breast cancer versus DCIS in different age groups. BMC Cancer. 2014 Aug 11;14:584
[PubMed ID: 25112586]
Pooler BD Kim DH Lam VP Burnside ES Pickhardt PJ .
CT Colonography Reporting and Data System (C-RADS): benchmark values from a clinical screening program. AJR Am J Roentgenol. 2014 Jun;202(6):1232-7
[PubMed ID: 24848819]
Wu Y Alagoz O Vanness DJ Trentham-Dietz A Burnside ES .
Pursuing optimal thresholds to recommend breast biopsy by quantifying the value of tomosynthesis. Proc Soc Photo Opt Instrum Eng. 2014 Mar 11;9037:90370U
[PubMed ID: 25076829]
Wu Y Rubin DL Woods RW Elezaby M Burnside ES .
Developing a comprehensive database management system for organization and evaluation of mammography datasets. Cancer Inform. 2014;13(Suppl 3):53-62
[PubMed ID: 25368510]
Burnside ES Lin Y Munoz del Rio A Pickhardt PJ Wu Y Strigel RM Elezaby MA Kerr EA Miglioretti DL .
Addressing the challenge of assessing physician-level screening performance: mammography as an example. PLoS One. 2014;9(2):e89418
[PubMed ID: 24586763]
Wu Y Alagoz O Ayvaci MU Munoz Del Rio A Vanness DJ Woods R Burnside ES .
A comprehensive methodology for determining the most informative mammographic features. J Digit Imaging. 2013 Oct;26(5):941-7
[PubMed ID: 23503987]
Alagoz O Chhatwal J Burnside ES .
Optimal Policies for Reducing Unnecessary Follow-up Mammography Exams in Breast Cancer Diagnosis. Decis Anal. 2013 Sep;10(3):200-224
[PubMed ID: 24501588]
Pooler BD Kim DH Hassan C Rinaldi A Burnside ES Pickhardt PJ .
Variation in diagnostic performance among radiologists at screening CT colonography. Radiology. 2013 Jul;268(1):127-34
[PubMed ID: 23449954]
Liu J Page D Nassif H Shavlik J Peissig P McCarty C Onitilo AA Burnside E .
Genetic variants improve breast cancer risk prediction on mammograms. AMIA Annu Symp Proc. 2013;2013:876-85
[PubMed ID: 24551380]
Caretta-Weyer H Sisney GA Beckman C Burnside ES Salkowsi LR Strigel RM Wilke LG Neuman HB .
Impact of axillary ultrasound and core needle biopsy on the utility of intraoperative frozen section analysis and treatment decision making in women with invasive breast cancer. Am J Surg. 2012 Sep;204(3):308-14
[PubMed ID: 22483606]
Ayvaci MU Alagoz O Burnside ES .
The Effect of Budgetary Restrictions on Breast Cancer Diagnostic Decisions. Manuf Serv Oper Manag. 2012 Apr;14(4):600-617
[PubMed ID: 24027436]
Nassif H Wu Y Page D Burnside E .
Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women. AMIA Annu Symp Proc. 2012;2012:1330-9
[PubMed ID: 23304412]
Liu J Peissig P Zhang C Burnside E McCarty C Page D .
High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. JMLR Workshop Conf Proc. 2012;22:712-721
[PubMed ID: 23606924]
Burnside ES Chhatwal J Alagoz O .
What is the optimal threshold at which to recommend breast biopsy? PLoS One. 2012;7(11):e48820
[PubMed ID: 23144986]
Nassif H Cunha F Moreira IC Cruz-Correia R Sousa E Page D Burnside E Dutra I .
Extracting BI-RADS Features from Portuguese Clinical Texts. Proceedings (IEEE Int Conf Bioinformatics Biomed). 2012;:1-4
[PubMed ID: 23797461]
Ferreira P Fonseca NA Dutra I Woods R Burnside E .
Predicting Malignancy from Mammography Findings and Surgical Biopsies. Proceedings (IEEE Int Conf Bioinformatics Biomed). 2011 Nov;2011
[PubMed ID: 24363962]
Woods RW Sisney GS Salkowski LR Shinki K Lin Y Burnside ES .
The mammographic density of a mass is a significant predictor of breast cancer. Radiology. 2011 Feb;258(2):417-25
[PubMed ID: 21177388]