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Elizabeth S Burnside

Showing results (81-90 of 127) with videos related to

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Proceedings of Spie--The International Society for Optical Engineering|May 1, 2018
Quantifying predictive capability of electronic health records for the most harmful breast cancerYirong Wu, Jun Fan, Peggy Peissig, et al.
BMC Cancer|August 13, 2014
Predicting invasive breast cancer versus DCIS in different age groupsMehmet U S Ayvaci, Oguzhan Alagoz, Jagpreet Chhatwal, et al.
American Journal of Surgery|April 10, 2012
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 cancerHolly Caretta-Weyer, Gale A Sisney, Catherine Beckman, et al.
Breast (Edinburgh, Scotland)|September 7, 2014
Online support: Impact on anxiety in women who experience an abnormal screening mammogramEniola T Obadina, Lori L Dubenske, Helene E McDowell, et al.
Journal of the American College of Radiology : JACR|November 3, 2023
The Importance of Outcomes Ascertainment for Accurate Assessment of the Mammography Screening Cancer Detection Rate: A Simulation StudyElizabeth S Burnside, Michael R Lasarev, Brian L Sprague, et al.
Radiology|June 12, 2019
Age-based versus Risk-based Mammography Screening in Women 40-49 Years Old: A Cross-sectional StudyElizabeth S Burnside, Amy Trentham-Dietz, Christina M Shafer, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 1, 2019
Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variantsShara I Feld, Kaitlin M Woo, Roxana Alexandridis, et al.
Hormones & Cancer|February 15, 2011
Circulating sex hormones and mammographic breast density among postmenopausal womenBrian L Sprague, Amy Trentham-Dietz, Ronald E Gangnon, et al.
Radiology|April 16, 2009
Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findingsElizabeth S Burnside, Jesse Davis, Jagpreet Chhatwal, et al.
Radiology|October 18, 2007
Differentiating benign from malignant solid breast masses with US strain imagingElizabeth S Burnside, Timothy J Hall, Amy M Sommer, et al.
Pageof 13

Showing results (81-90 of 127) with videos related to

Sort By:
Pageof 13
Proceedings of Spie--The International Society for Optical Engineering|May 1, 2018
Quantifying predictive capability of electronic health records for the most harmful breast cancerYirong Wu, Jun Fan, Peggy Peissig, et al.
BMC Cancer|August 13, 2014
Predicting invasive breast cancer versus DCIS in different age groupsMehmet U S Ayvaci, Oguzhan Alagoz, Jagpreet Chhatwal, et al.
American Journal of Surgery|April 10, 2012
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 cancerHolly Caretta-Weyer, Gale A Sisney, Catherine Beckman, et al.
Breast (Edinburgh, Scotland)|September 7, 2014
Online support: Impact on anxiety in women who experience an abnormal screening mammogramEniola T Obadina, Lori L Dubenske, Helene E McDowell, et al.
Journal of the American College of Radiology : JACR|November 3, 2023
The Importance of Outcomes Ascertainment for Accurate Assessment of the Mammography Screening Cancer Detection Rate: A Simulation StudyElizabeth S Burnside, Michael R Lasarev, Brian L Sprague, et al.
Radiology|June 12, 2019
Age-based versus Risk-based Mammography Screening in Women 40-49 Years Old: A Cross-sectional StudyElizabeth S Burnside, Amy Trentham-Dietz, Christina M Shafer, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|March 1, 2019
Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variantsShara I Feld, Kaitlin M Woo, Roxana Alexandridis, et al.
Hormones & Cancer|February 15, 2011
Circulating sex hormones and mammographic breast density among postmenopausal womenBrian L Sprague, Amy Trentham-Dietz, Ronald E Gangnon, et al.
Radiology|April 16, 2009
Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findingsElizabeth S Burnside, Jesse Davis, Jagpreet Chhatwal, et al.
Radiology|October 18, 2007
Differentiating benign from malignant solid breast masses with US strain imagingElizabeth S Burnside, Timothy J Hall, Amy M Sommer, et al.
Pageof 13