Search research articles
Contact Us
Filters
Showing results (11-20 of 56) with videos related to
Page
of 6
Sort By:
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|
June 2, 2018
Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality
Sharon E Davis, Thomas A Lasko, Guanhua Chen, et al.
Journal of Biomedical Informatics
|
October 4, 2005
The use of receiver operating characteristic curves in biomedical informatics
Thomas A Lasko, Jui G Bhagwat, Kelly H Zou, et al.
Journal of the American Medical Informatics Association : JAMIA
|
December 5, 2020
SynTEG: a framework for temporal structured electronic health data simulation
Ziqi Zhang, Chao Yan, Thomas A Lasko, et al.
Journal of Biomedical Informatics
|
September 20, 2015
A study of active learning methods for named entity recognition in clinical text
Yukun Chen, Thomas A Lasko, Qiaozhu Mei, et al.
Journal of the American Medical Informatics Association : JAMIA
|
October 14, 2005
Automated identification of a physician's primary patients
Thomas A Lasko, Steven J Atlas, Michael J Barry, et al.
Journal of Medical Systems
|
May 31, 2018
A System for Automated Determination of Perioperative Patient Acuity
Linda Zhang, Daniel Fabbri, Thomas A Lasko, et al.
Journal of the American Medical Informatics Association : JAMIA
|
April 6, 2017
Calibration drift in regression and machine learning models for acute kidney injury
Sharon E Davis, Thomas A Lasko, Guanhua Chen, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|
April 21, 2020
Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating
Sharon E Davis, Robert A Greevy, Thomas A Lasko, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|
May 9, 2015
Machine learning for risk prediction of acute coronary syndrome
Jacob P VanHouten, John M Starmer, Nancy M Lorenzi, et al.
Journal of Biomedical Informatics
|
November 6, 2020
Detection of calibration drift in clinical prediction models to inform model updating
Sharon E Davis, Robert A Greevy, Thomas A Lasko, et al.
Page
of 6
Search research articles
Search
Showing results (11-20 of 56) with videos related to
Sort By:
Page
of 6
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|
June 2, 2018
Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality
Sharon E Davis, Thomas A Lasko, Guanhua Chen, et al.
Journal of Biomedical Informatics
|
October 4, 2005
The use of receiver operating characteristic curves in biomedical informatics
Thomas A Lasko, Jui G Bhagwat, Kelly H Zou, et al.
Journal of the American Medical Informatics Association : JAMIA
|
December 5, 2020
SynTEG: a framework for temporal structured electronic health data simulation
Ziqi Zhang, Chao Yan, Thomas A Lasko, et al.
Journal of Biomedical Informatics
|
September 20, 2015
A study of active learning methods for named entity recognition in clinical text
Yukun Chen, Thomas A Lasko, Qiaozhu Mei, et al.
Journal of the American Medical Informatics Association : JAMIA
|
October 14, 2005
Automated identification of a physician's primary patients
Thomas A Lasko, Steven J Atlas, Michael J Barry, et al.
Journal of Medical Systems
|
May 31, 2018
A System for Automated Determination of Perioperative Patient Acuity
Linda Zhang, Daniel Fabbri, Thomas A Lasko, et al.
Journal of the American Medical Informatics Association : JAMIA
|
April 6, 2017
Calibration drift in regression and machine learning models for acute kidney injury
Sharon E Davis, Thomas A Lasko, Guanhua Chen, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|
April 21, 2020
Comparison of Prediction Model Performance Updating Protocols: Using a Data-Driven Testing Procedure to Guide Updating
Sharon E Davis, Robert A Greevy, Thomas A Lasko, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|
May 9, 2015
Machine learning for risk prediction of acute coronary syndrome
Jacob P VanHouten, John M Starmer, Nancy M Lorenzi, et al.
Journal of Biomedical Informatics
|
November 6, 2020
Detection of calibration drift in clinical prediction models to inform model updating
Sharon E Davis, Robert A Greevy, Thomas A Lasko, et al.
Page
of 6