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Elizabeth S Burnside

Showing results (41-50 of 127) with videos related to

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Cancer|June 22, 2010
Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibrationTurgay Ayer, Oguzhan Alagoz, Jagpreet Chhatwal, et al.
Journal of the American College of Radiology : JACR|January 12, 2025
Artificial Intelligence in Radiology: A Leadership SurveyElizabeth S Burnside, Thomas M Grist, Michael R Lasarev, et al.
AJR. American Journal of Roentgenology|January 23, 2004
A probabilistic expert system that provides automated mammographic-histologic correlation: initial experienceElizabeth S Burnside, Daniel L Rubin, Ross D Shachter, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|November 11, 2009
Informatics in radiology: comparison of logistic regression and artificial neural network models in breast cancer risk estimationTurgay Ayer, Jagpreet Chhatwal, Oguzhan Alagoz, et al.
AJR. American Journal of Roentgenology|May 23, 2014
CT Colonography Reporting and Data System (C-RADS): benchmark values from a clinical screening programB Dustin Pooler, David H Kim, Vu P Lam, et al.
Journal of Breast Imaging|August 3, 2024
Methodological Considerations in Evaluating Breast Cancer Screening StudiesAnand K Narayan, Randy C Miles, Ryan W Woods, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|May 9, 2015
Comparing the value of mammographic features and genetic variants in breast cancer risk predictionYirong Wu, Jie Liu, David Page, et al.
Radiology|March 2, 2013
Variation in diagnostic performance among radiologists at screening CT colonographyB Dustin Pooler, David H Kim, Cesare Hassan, et al.
Radiology|December 24, 2010
The mammographic density of a mass is a significant predictor of breast cancerRyan W Woods, Gale S Sisney, Lonie R Salkowski, et al.
AJR. American Journal of Roentgenology|March 24, 2009
A logistic regression model based on the national mammography database format to aid breast cancer diagnosisJagpreet Chhatwal, Oguzhan Alagoz, Mary J Lindstrom, et al.
Pageof 13

Showing results (41-50 of 127) with videos related to

Sort By:
Pageof 13
Cancer|June 22, 2010
Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibrationTurgay Ayer, Oguzhan Alagoz, Jagpreet Chhatwal, et al.
Journal of the American College of Radiology : JACR|January 12, 2025
Artificial Intelligence in Radiology: A Leadership SurveyElizabeth S Burnside, Thomas M Grist, Michael R Lasarev, et al.
AJR. American Journal of Roentgenology|January 23, 2004
A probabilistic expert system that provides automated mammographic-histologic correlation: initial experienceElizabeth S Burnside, Daniel L Rubin, Ross D Shachter, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|November 11, 2009
Informatics in radiology: comparison of logistic regression and artificial neural network models in breast cancer risk estimationTurgay Ayer, Jagpreet Chhatwal, Oguzhan Alagoz, et al.
AJR. American Journal of Roentgenology|May 23, 2014
CT Colonography Reporting and Data System (C-RADS): benchmark values from a clinical screening programB Dustin Pooler, David H Kim, Vu P Lam, et al.
Journal of Breast Imaging|August 3, 2024
Methodological Considerations in Evaluating Breast Cancer Screening StudiesAnand K Narayan, Randy C Miles, Ryan W Woods, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|May 9, 2015
Comparing the value of mammographic features and genetic variants in breast cancer risk predictionYirong Wu, Jie Liu, David Page, et al.
Radiology|March 2, 2013
Variation in diagnostic performance among radiologists at screening CT colonographyB Dustin Pooler, David H Kim, Cesare Hassan, et al.
Radiology|December 24, 2010
The mammographic density of a mass is a significant predictor of breast cancerRyan W Woods, Gale S Sisney, Lonie R Salkowski, et al.
AJR. American Journal of Roentgenology|March 24, 2009
A logistic regression model based on the national mammography database format to aid breast cancer diagnosisJagpreet Chhatwal, Oguzhan Alagoz, Mary J Lindstrom, et al.
Pageof 13