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Paper Details

Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention.
JAMA Netw Open
44
2019
Participants, patient, patients
Author NameAffiliation
Bobak J MortazaviTexas A&M University, College Station.
Bobak J MortazaviCenter for Outcomes Research and Evaluation, Yale New Haven Hospital
Bobak J MortazaviYale School of Medicine
Bobak J MortazaviCenter for Remote Health Technologies and Systems, Texas A&M University, College Station.
Bobak J MortazaviTexas A&M University, College Station.
Bobak J MortazaviCenter for Remote Health Technologies and Systems, Texas A&M University, College Station.
Bobak J MortazaviYale School of Medicine
Bobak J MortazaviCenter for Outcomes Research and Evaluation, Yale New Haven Hospital
Chenxi HuangYale School of Medicine
Chenxi HuangCenter for Outcomes Research and Evaluation, Yale New Haven Hospital
Jeptha P CurtisYale School of Medicine
Jeptha P CurtisCenter for Outcomes Research and Evaluation, Yale New Haven Hospital
Frederick A MasoudiUniversity of Colorado Anschutz Medical Campus
Richard E ShawCalifornia Pacific Medical Center
Harlan M KrumholzYale School of Medicine
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale New Haven Hospital
Harlan M KrumholzYale School of Public Health
Harlan M KrumholzYale School of Medicine
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale New Haven Hospital
Harlan M KrumholzYale School of Public Health
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