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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.
American Journal of Public Health|August 10, 2013
Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithmsNicholas S Roetker, C David Page, James A Yonker, 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.
Circulation. Arrhythmia and Electrophysiology|January 13, 2018
Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION TrialMatthew M Kalscheur, Ryan T Kipp, Matthew C Tattersall, et al.
The Journal of Allergy and Clinical Immunology|October 22, 2013
Childhood asthma clusters and response to therapy in clinical trialsTimothy S Chang, Robert F Lemanske, David T Mauger, et al.
The Journal of Allergy and Clinical Immunology. in Practice|November 5, 2013
Evaluation of the modified asthma predictive index in high-risk preschool childrenTimothy S Chang, Robert F Lemanske, Theresa W Guilbert, et al.
Academic Radiology|October 31, 2015
Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast BiopsyElizabeth S Burnside, Jie Liu, Yirong Wu, et al.
Journal of Biomedical Informatics|December 24, 2014
Sparse modeling of spatial environmental variables associated with asthmaTimothy S Chang, Ronald E Gangnon, C David Page, et al.
Optometry and Vision Science : Official Publication of the American Academy of Optometry|July 12, 2014
Cone structure in subjects with known genetic relative risk for AMDMegan E Land, Robert F Cooper, Jonathon Young, et al.
Proceedings of the National Academy of Sciences of the United States of America|September 23, 2015
Human pluripotent stem cell-derived neural constructs for predicting neural toxicityMichael P Schwartz, Zhonggang Hou, Nicholas E Propson, et al.
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Showing results (11-20 of 20) with videos related to

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Pageof 2
You have reached the last page of results.This site can display upto 20 results.
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.
American Journal of Public Health|August 10, 2013
Assessment of genetic and nongenetic interactions for the prediction of depressive symptomatology: an analysis of the Wisconsin Longitudinal Study using machine learning algorithmsNicholas S Roetker, C David Page, James A Yonker, 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.
Circulation. Arrhythmia and Electrophysiology|January 13, 2018
Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION TrialMatthew M Kalscheur, Ryan T Kipp, Matthew C Tattersall, et al.
The Journal of Allergy and Clinical Immunology|October 22, 2013
Childhood asthma clusters and response to therapy in clinical trialsTimothy S Chang, Robert F Lemanske, David T Mauger, et al.
The Journal of Allergy and Clinical Immunology. in Practice|November 5, 2013
Evaluation of the modified asthma predictive index in high-risk preschool childrenTimothy S Chang, Robert F Lemanske, Theresa W Guilbert, et al.
Academic Radiology|October 31, 2015
Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast BiopsyElizabeth S Burnside, Jie Liu, Yirong Wu, et al.
Journal of Biomedical Informatics|December 24, 2014
Sparse modeling of spatial environmental variables associated with asthmaTimothy S Chang, Ronald E Gangnon, C David Page, et al.
Optometry and Vision Science : Official Publication of the American Academy of Optometry|July 12, 2014
Cone structure in subjects with known genetic relative risk for AMDMegan E Land, Robert F Cooper, Jonathon Young, et al.
Proceedings of the National Academy of Sciences of the United States of America|September 23, 2015
Human pluripotent stem cell-derived neural constructs for predicting neural toxicityMichael P Schwartz, Zhonggang Hou, Nicholas E Propson, et al.
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