Research Topics
| Elizabeth BurnsideSummaryAffiliation: University of Wisconsin Country: USA Publications
Research Grants
| Collaborators
|
Detail Information
Publications
What is the optimal threshold at which to recommend breast biopsy?Elizabeth S Burnside
Department of Radiology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin, USA
PLoS ONE 7:e48820. 2012..We use a sequential decision analytic model considering clinical and mammography features to determine the optimal general threshold for image guided breast biopsy and the sensitivity of this threshold to variation of these features...- The ACR BI-RADS experience: learning from historyElizabeth S Burnside
Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53792 3252, USA
J Am Coll Radiol 6:851-60. 2009..The history of this lexicon illustrates a series of challenges and instructive successes that provide a valuable guide for other groups that aspire to develop similar lexicons in the future... 
Use of microcalcification descriptors in BI-RADS 4th edition to stratify risk of malignancyElizabeth S Burnside
Department of Radiology, University of Wisconsin Medical School, E3 311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792 3252, USA
Radiology 242:388-95. 2007....- Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findingsElizabeth S Burnside
Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3 311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792 3252, USA
Radiology 251:663-72. 2009.... - Differentiating benign from malignant solid breast masses with US strain imagingElizabeth S Burnside
Department of Radiology, University of Wisconsin Medical School, E3 311 Clinical Science Center, Madison, WI 53792 3252, USA
Radiology 245:401-10. 2007..To prospectively evaluate the sensitivity and specificity of ultrasonographic (US) strain imaging for distinguishing between benign and malignant solid breast masses, with biopsy results as the reference standard... - Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experienceElizabeth S Burnside
Department of Radiology, University of Wisconsin Medical School, E3 311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792 3252, USA
Radiology 240:666-73. 2006.... - A logistic regression model based on the national mammography database format to aid breast cancer diagnosisJagpreet Chhatwal
Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3 311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792 3252, USA
AJR Am J Roentgenol 192:1117-27. 2009..The purpose of our study was to create a breast cancer risk estimation model based on the descriptors of the National Mammography Database using logistic regression that can aid in decision making for the early detection of breast cancer... - A probabilistic expert system that provides automated mammographic-histologic correlation: initial experienceElizabeth S Burnside
Department of Radiology, University of California School of Medicine, Box 1667, San Francisco, CA 94143 1667, USA
AJR Am J Roentgenol 182:481-8. 2004.... - Using a Bayesian network to predict the probability and type of breast cancer represented by microcalcifications on mammographyElizabeth S Burnside
Department of Radiology, University of Wisconsin Medical School, 600 Highland Avenue, Madison, WI 53792, USA
Stud Health Technol Inform 107:13-7. 2004.... - Validation of results from knowledge discovery: mass density as a predictor of breast cancerRyan W Woods
Department of Radiology, University of Wisconsin School of Medicine and Public Health, E3 366 Clinical Science Center, 600 Highland Ave, Madison, WI 53792 3252, USA
J Digit Imaging 23:554-61. 2010..Both ILP and conditional probabilities show that high breast mass density is an important adjunct predictor of malignancy, and this association is confirmed in an independent data set of prospectively collected mammographic findings... - Fluorescence spectroscopy: an adjunct diagnostic tool to image-guided core needle biopsy of the breastChangfang Zhu
Department of Electrical and Computer Engineering, University of Wisconsin, Madison, WI 53706, USA
IEEE Trans Biomed Eng 56:2518-28. 2009..This study demonstrates the feasibility of performing fluorescence spectroscopy during clinical core needle breast biopsy, and the potential of this technique for identifying breast malignancy in vivo... - Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibrationTurgay Ayer
Industrial and Systems Engineering Department, University of Wisconsin, Madison, Wisconsin 53792 3252, USA
Cancer 116:3310-21. 2010.... 
Informatics in radiology: comparison of logistic regression and artificial neural network models in breast cancer risk estimationTurgay Ayer
Departments of Industrial and Systems Engineering, Radiology, and Biostatistics and Medical Informatics, University of Wisconsin, 1513 University Ave, Madison, WI 53706 1572, USA
Radiographics 30:13-22. 2010..Although they demonstrated similar performance, the two models have unique characteristics-strengths as well as limitations-that must be considered and may prove complementary in contributing to improved clinical decision making...- Interpreting data from audits when screening and diagnostic mammography outcomes are combinedRita E Sohlich
Department of Radiology, Box 1667, University of California Medical Center, San Francisco, CA 94143-1667, USA
AJR Am J Roentgenol 178:681-6. 2002.... - Differential value of comparison with previous examinations in diagnostic versus screening mammographyElizabeth S Burnside
Department of Radiology, Box 1667, University of California School of Medicine, San Francisco, CA 94143-1667, USA
AJR Am J Roentgenol 179:1173-7. 2002..For diagnostic mammography, comparison with previous examinations increases true-positive findings... - Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older womenHoussam Nassif
University of Wisconsin, Madison, USA
AMIA Annu Symp Proc 2012:1330-9. 2012..In addition, LDP-BN offers valuable insight into the classification process, revealing novel older-specific rules that link mass presence to invasive, and calcification presence and lack of detectable mass to DCIS... - Toward best practices in radiology reportingCharles E Kahn
Department of Radiology, Medical College of Wisconsin, 9200 W Wisconsin Ave, Milwaukee, WI 53226, USA
Radiology 252:852-6. 2009..The committee's charter provides an opportunity to improve the organization, content, readability, and usefulness of the radiology report and to advance the efficiency and effectiveness of the reporting process... - American College Of Radiology/Society of Breast Imaging curriculum for resident and fellow education in breast imagingEdward A Sickles
University of California, San Francisco, Medical Center, Department of Radiology, San Francisco, CA 94143 1667, USA
J Am Coll Radiol 3:879-84. 2006..Radiologists already in practice also may find the curriculum useful in outlining the material they need to know to remain up to date in the practice of breast imaging... - The use of batch reading to improve the performance of screening mammographyElizabeth S Burnside
Breast Care Center, University of Wisconsin Medical School, Madison, WI 53792-1804, USA
AJR Am J Roentgenol 185:790-6. 2005..CONCLUSION: Our experience shows that batch reading can significantly reduce screening mammography recall rates without affecting the cancer detection rate or the proportion of cancers diagnosed with favorable prognostic indicators... - Bayesian networks: computer-assisted diagnosis support in radiologyElizabeth S Burnside
University of Wisconsin Medical School, Department of Radiology, E3 311 Clinical Science Center, 600 Highland Avenue, Madison, WI 53792 3252, USA
Acad Radiol 12:422-30. 2005.... - Socioeconomic disparities in the decline in invasive breast cancer incidenceBrian L Sprague
University of Wisconsin Carbone Comprehensive Cancer Center, 610 Walnut St, WARF Rm 307, Madison, WI 53726, USA
Breast Cancer Res Treat 122:873-8. 2010..These results are consistent with the hypothesis that a saturation of screening mammography utilization contributed to the overall decline in breast cancer incidence... - Patient, faculty, and self-assessment of radiology resident performance: a 360-degree method of measuring professionalism and interpersonal/communication skillsJonathan Wood
Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, WI 53792, USA
Acad Radiol 11:931-9. 2004..Requiring only a specified number of assessments per rotation would make the process less burdensome for residents and faculty...
Research Grants
- Machine Learning for Improved Mammography ScreeningElizabeth Burnside; Fiscal Year: 2009....
- Machine Learning for Improved Mammography ScreeningElizabeth S Burnside; Fiscal Year: 2010....
- Machine Learning for Improved Mammography ScreeningElizabeth Burnside; Fiscal Year: 2009....