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Paper Details

Can machine learning complement traditional medical device surveillance? A case study of dual-chamber implantable cardioverter-defibrillators.
Med Devices (Auckl)
10
2017
Author NameAffiliation
Joseph S Ross
Joseph S RossCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Joseph S RossYale School of Public Health.
Joseph S RossRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine.
Joseph G AkarYale School of Medicine
Joseph G AkarCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Jeptha P CurtisCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Jeptha P CurtisYale School of Medicine
Ginger M GambleCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Shu-Xia LiCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Danica Marinac-DabicCenter for Devices and Radiological Health
Frederick A MasoudiUniversity of Colorado
Sharon-Lise T NormandHarvard Medical School.
Sharon-Lise T NormandHarvard TH Chan School of Public Health
Richard E ShawCalifornia Pacific Medical Center
Harlan M KrumholzRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine.
Harlan M KrumholzYale School of Public Health.
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Harlan M KrumholzYale School of Medicine
Harlan M KrumholzRobert Wood Johnson Foundation Clinical Scholars Program, Yale School of Medicine.
Harlan M KrumholzYale School of Public Health.
Harlan M KrumholzCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital.
Harlan M KrumholzYale School of Medicine
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