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Jennifer A Mattera

Showing results (31-40 of 36) with videos related to

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Journal of the American College of Cardiology|October 4, 2005
Achieving door-to-balloon times that meet quality guidelines: how do successful hospitals do it?Elizabeth H Bradley, Sarah A Roumanis, Martha J Radford, et al.
The New England Journal of Medicine|November 15, 2006
Strategies for reducing the door-to-balloon time in acute myocardial infarctionElizabeth H Bradley, Jeph Herrin, Yongfei Wang, et al.
Circulation. Cardiovascular Quality and Outcomes|December 25, 2009
An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failurePatricia S Keenan, Sharon-Lise T Normand, Zhenqiu Lin, et al.
Global Pediatrics|September 20, 2024
Leveraging machine learning to study how temperament scores predict pre-term birth statusErich Seamon, Jennifer A Mattera, Sarah A Keim, et al.
Plos One|April 13, 2022
Using machine learning to understand age and gender classification based on infant temperamentMaria A Gartstein, D Erich Seamon, Jennifer A Mattera, et al.
Plos One|December 17, 2024
Correction: Using machine learning to understand age and gender classification based on infant temperamentMaria A Gartstein, D Erich Seamon, Jennifer A Mattera, et al.
Pageof 4

Showing results (31-40 of 36) with videos related to

Sort By:
Pageof 4
You have reached the last page of results.This site can display upto 36 results.
Journal of the American College of Cardiology|October 4, 2005
Achieving door-to-balloon times that meet quality guidelines: how do successful hospitals do it?Elizabeth H Bradley, Sarah A Roumanis, Martha J Radford, et al.
The New England Journal of Medicine|November 15, 2006
Strategies for reducing the door-to-balloon time in acute myocardial infarctionElizabeth H Bradley, Jeph Herrin, Yongfei Wang, et al.
Circulation. Cardiovascular Quality and Outcomes|December 25, 2009
An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failurePatricia S Keenan, Sharon-Lise T Normand, Zhenqiu Lin, et al.
Global Pediatrics|September 20, 2024
Leveraging machine learning to study how temperament scores predict pre-term birth statusErich Seamon, Jennifer A Mattera, Sarah A Keim, et al.
Plos One|April 13, 2022
Using machine learning to understand age and gender classification based on infant temperamentMaria A Gartstein, D Erich Seamon, Jennifer A Mattera, et al.
Plos One|December 17, 2024
Correction: Using machine learning to understand age and gender classification based on infant temperamentMaria A Gartstein, D Erich Seamon, Jennifer A Mattera, et al.
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