Elizabeth Burnside

Summary

Affiliation: University of Wisconsin
Country: USA

Publications

  1. pmc 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
  2. ncbi request reprint Differentiating benign from malignant solid breast masses with US strain imaging
    Elizabeth 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
  3. ncbi request reprint Use of microcalcification descriptors in BI-RADS 4th edition to stratify risk of malignancy
    Elizabeth 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
  4. pmc The ACR BI-RADS experience: learning from history
    Elizabeth 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
  5. pmc Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings
    Elizabeth 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
  6. pmc Validation of results from knowledge discovery: mass density as a predictor of breast cancer
    Ryan 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
  7. pmc Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women
    Houssam Nassif
    University of Wisconsin, Madison, USA
    AMIA Annu Symp Proc 2012:1330-9. 2012
  8. ncbi request reprint Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience
    Elizabeth 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
  9. ncbi request reprint A probabilistic expert system that provides automated mammographic-histologic correlation: initial experience
    Elizabeth 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
  10. pmc A logistic regression model based on the national mammography database format to aid breast cancer diagnosis
    Jagpreet 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

Research Grants

  1. Machine Learning for Improved Mammography Screening
    Elizabeth Burnside; Fiscal Year: 2009
  2. Machine Learning for Improved Mammography Screening
    Elizabeth S Burnside; Fiscal Year: 2010
  3. Machine Learning for Improved Mammography Screening
    Elizabeth Burnside; Fiscal Year: 2009

Collaborators

Detail Information

Publications22

  1. pmc 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...
  2. ncbi request reprint Differentiating benign from malignant solid breast masses with US strain imaging
    Elizabeth 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...
  3. ncbi request reprint Use of microcalcification descriptors in BI-RADS 4th edition to stratify risk of malignancy
    Elizabeth 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
    ....
  4. pmc The ACR BI-RADS experience: learning from history
    Elizabeth 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...
  5. pmc Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings
    Elizabeth 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
    ....
  6. pmc Validation of results from knowledge discovery: mass density as a predictor of breast cancer
    Ryan 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...
  7. pmc Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women
    Houssam 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...
  8. ncbi request reprint Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: initial experience
    Elizabeth 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
    ....
  9. ncbi request reprint A probabilistic expert system that provides automated mammographic-histologic correlation: initial experience
    Elizabeth 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
    ....
  10. pmc A logistic regression model based on the national mammography database format to aid breast cancer diagnosis
    Jagpreet 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...
  11. ncbi request reprint Using a Bayesian network to predict the probability and type of breast cancer represented by microcalcifications on mammography
    Elizabeth 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
    ....
  12. pmc Fluorescence spectroscopy: an adjunct diagnostic tool to image-guided core needle biopsy of the breast
    Changfang 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...
  13. ncbi request reprint Interpreting data from audits when screening and diagnostic mammography outcomes are combined
    Rita 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
    ....
  14. ncbi request reprint Differential value of comparison with previous examinations in diagnostic versus screening mammography
    Elizabeth 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
    ..The purpose of our study was to analyze the differences in clinical outcomes of diagnostic and screening mammography depending on whether comparison is made with previous examinations...
  15. pmc Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration
    Turgay Ayer
    Industrial and Systems Engineering Department, University of Wisconsin, Madison, Wisconsin 53792 3252, USA
    Cancer 116:3310-21. 2010
    ....
  16. pmc Informatics in radiology: comparison of logistic regression and artificial neural network models in breast cancer risk estimation
    Turgay 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...
  17. pmc Socioeconomic disparities in the decline in invasive breast cancer incidence
    Brian 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...
  18. ncbi request reprint American College Of Radiology/Society of Breast Imaging curriculum for resident and fellow education in breast imaging
    Edward 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...
  19. ncbi request reprint Bayesian networks: computer-assisted diagnosis support in radiology
    Elizabeth 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
    ....
  20. doi request reprint Toward best practices in radiology reporting
    Charles 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...
  21. ncbi request reprint The use of batch reading to improve the performance of screening mammography
    Elizabeth S Burnside
    Breast Care Center, University of Wisconsin Medical School, Madison, WI 53792 1804, USA
    AJR Am J Roentgenol 185:790-6. 2005
    ..The objective of our study was to prove that batch reading of screening mammograms can reduce recall rates without sacrificing cancer detection...
  22. ncbi request reprint Patient, faculty, and self-assessment of radiology resident performance: a 360-degree method of measuring professionalism and interpersonal/communication skills
    Jonathan Wood
    Department of Radiology, University of Wisconsin Hospital and Clinics, Madison, WI 53792, USA
    Acad Radiol 11:931-9. 2004
    ..To develop and test the reliability, validity, and feasibility of a 360-degree evaluation to measure radiology resident competence in professionalism and interpersonal/communication skills...

Research Grants5

  1. Machine Learning for Improved Mammography Screening
    Elizabeth Burnside; Fiscal Year: 2009
    ....
  2. Machine Learning for Improved Mammography Screening
    Elizabeth S Burnside; Fiscal Year: 2010
    ....
  3. Machine Learning for Improved Mammography Screening
    Elizabeth Burnside; Fiscal Year: 2009
    ....