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BMC Health Services Research
|
June 30, 2022
Can diverse population characteristics be leveraged in a machine learning pipeline to predict resource intensive healthcare utilization among hospital service areas?
Iben M Ricket, Todd A MacKenzie, Jennifer A Emond, et al.
Intelligence-Based Medicine
|
July 21, 2023
Novel integration of governmental data sources using machine learning to identify super-utilization among U.S. counties
Iben M Ricket, Michael E Matheny, Todd A MacKenzie, et al.
BMC Public Health
|
November 18, 2022
Quantifying differences in packaged food and drink purchases among households with diet-related cardiometabolic multi-morbidity: a cross-sectional analysis
Iben M Ricket, Jeremiah R Brown, Todd A MacKenzie, et al.
JMIR Medical Informatics
|
May 12, 2026
Scalable Identification of Clinically Relevant Chronic Obstructive Pulmonary Disease Documents in Large-Scale Electronic Health Record Datasets With a Lightweight Natural Language Processing Model: Retrospective Cohort Study
Mohammed Al-Garadi, Sharon E Davis, Michael E Matheny, et al.
Circulation. Cardiovascular Quality and Outcomes
|
May 30, 2020
Computable Phenotype Implementation for a National, Multicenter Pragmatic Clinical Trial: Lessons Learned From ADAPTABLE
Faraz S Ahmad, Iben M Ricket, Bradley G Hammill, et al.
Journal of the American Heart Association
|
March 24, 2022
Information Extraction From Electronic Health Records to Predict Readmission Following Acute Myocardial Infarction: Does Natural Language Processing Using Clinical Notes Improve Prediction of Readmission?
Jeremiah R Brown, Iben M Ricket, Ruth M Reeves, et al.
Journal of the American Heart Association
|
May 15, 2025
Sustained Improvements After Intervention to Prevent Contrast-Associated Acute Kidney Injury: A Randomized Controlled Trial
Michael E Matheny, Elizabeth Carpenter-Song, Iben M Ricket, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 7) with videos related to
Sort By:
Page
of 1
BMC Health Services Research
|
June 30, 2022
Can diverse population characteristics be leveraged in a machine learning pipeline to predict resource intensive healthcare utilization among hospital service areas?
Iben M Ricket, Todd A MacKenzie, Jennifer A Emond, et al.
Intelligence-Based Medicine
|
July 21, 2023
Novel integration of governmental data sources using machine learning to identify super-utilization among U.S. counties
Iben M Ricket, Michael E Matheny, Todd A MacKenzie, et al.
BMC Public Health
|
November 18, 2022
Quantifying differences in packaged food and drink purchases among households with diet-related cardiometabolic multi-morbidity: a cross-sectional analysis
Iben M Ricket, Jeremiah R Brown, Todd A MacKenzie, et al.
JMIR Medical Informatics
|
May 12, 2026
Scalable Identification of Clinically Relevant Chronic Obstructive Pulmonary Disease Documents in Large-Scale Electronic Health Record Datasets With a Lightweight Natural Language Processing Model: Retrospective Cohort Study
Mohammed Al-Garadi, Sharon E Davis, Michael E Matheny, et al.
Circulation. Cardiovascular Quality and Outcomes
|
May 30, 2020
Computable Phenotype Implementation for a National, Multicenter Pragmatic Clinical Trial: Lessons Learned From ADAPTABLE
Faraz S Ahmad, Iben M Ricket, Bradley G Hammill, et al.
Journal of the American Heart Association
|
March 24, 2022
Information Extraction From Electronic Health Records to Predict Readmission Following Acute Myocardial Infarction: Does Natural Language Processing Using Clinical Notes Improve Prediction of Readmission?
Jeremiah R Brown, Iben M Ricket, Ruth M Reeves, et al.
Journal of the American Heart Association
|
May 15, 2025
Sustained Improvements After Intervention to Prevent Contrast-Associated Acute Kidney Injury: A Randomized Controlled Trial
Michael E Matheny, Elizabeth Carpenter-Song, Iben M Ricket, et al.
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of 1