
Elizabeth Burnside
· ProfessorUniversity of Wisconsin-Madison · Radiology
Active 1989–2026
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About
Elizabeth S. Burnside, MD, MPH, FACR, is a professor of radiology at the University of Wisconsin School of Medicine and Public Health, where she also serves as Associate Dean for team science and interdisciplinary research. She specializes in breast imaging and is a champion for leveraging innovation to improve clinical care. Dr. Burnside combines her medical training with interests in public health and computer science, focusing on developing and utilizing computational methods to enhance decision-making in breast imaging. She holds affiliate appointments in the departments of Biostatistics, Medical Informatics, and Population Health Sciences, facilitating her work in improving population-based screening and diagnosis of breast cancer.
Research topics
- Political Science
- Medicine
- Computer Science
- Data science
- Marketing
- Gynecology
- Radiology
- Business
- Physics
- Biology
Selected publications
A Population-Based Study of Genes Previously Implicated in Breast Cancer
New England Journal of Medicine · 2021 · 851 citations
BACKGROUND: Population-based estimates of the risk of breast cancer associated with germline pathogenic variants in cancer-predisposition genes are critically needed for risk assessment and management in women with inherited pathogenic variants. METHODS: In a population-based case-control study, we performed sequencing using a custom multigene amplicon-based panel to identify germline pathogenic variants in 28 cancer-predisposition genes among 32,247 women with breast cancer (case patients) and…
Radiology · 2020 · 75 citations
See also the editorial by Moy in this issue.
Nature Medicine · 2025-04-03 · 20 citations
articleOpen accessNEJM AI · 2025-11-26 · 19 citations
articleOpen accessBACKGROUND: Electronic health record (EHR) documentation is a major contributor to work-related practitioner exhaustion and the interpersonal disengagement known as burnout. Generative artificial intelligence (AI) scribes that passively capture clinical conversations and draft visit notes may alleviate this burden, but evidence remains limited. METHODS: A 24-week, stepped-wedge, individually randomized pragmatic trial was conducted across ambulatory clinics in two states. Sixty-six health care p…
NEJM AI · 2025-08-28 · 17 citations
articleOpen accessBACKGROUND: Ambient artificial intelligence (AI) offers the potential to reduce documentation burden and improve efficiency through clinical note generation. Widespread adoption, however, remains limited due to challenges in electronic health record (EHR) integration, coding compliance, and real-world evaluation. This study introduces a framework and protocols to design, monitor, and deploy ambient AI within routine care. METHODS: , Tenth Revision (ICD-10) compliance were performed using an inte…
Recent grants
Mentoring And Research In Patient-Oriented Breast Cancer Diagnosis
NIH · $963k · 2015–2020
Integrating Machine Learning and Physician Expertise for Breast Cancer Diagnosis
NIH · $1.2M · 2011–2016
NIH · $1.4M · 2012
Frequent coauthors
- 220 shared
Amy Trentham‐Dietz
University of Wisconsin Carbone Cancer Center
- 206 shared
Oğuzhan Alagöz
University of Wisconsin–Madison
- 181 shared
Natasha K. Stout
West Virginia University
- 176 shared
Sandra J. Lee
- 173 shared
Harry J. de Koning
Erasmus MC
- 173 shared
Hui Huang
First Affiliated Hospital of Chengdu Medical College
- 173 shared
Nicolien T. van Ravesteyn
Erasmus MC
- 172 shared
Mehmet Ali Ergün
Istanbul Technical University
Education
M.D., Medicine
University of Wisconsin–Madison
Other, Public Health
University of Wisconsin–Madison
Awards & honors
- 2023 Advancing Women in Medicine and Science Award from UW’s…
- RSNA Gold Medal (2024)
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