Can machine learning complement traditional medical device surveillance? A case-study of dual-chamber implantable cardioverter–defibrillators

Can machine learning complement traditional medical device surveillance? A case-study of dual-chamber implantable cardioverter–defibrillators

Joseph S Ross,1–4 Jonathan Bates,4 Craig S Parzynski,4 Joseph G Akar,4,5 Jeptha P Curtis,4,5 Nihar R Desai,4,5 James V Freeman,4,5 Ginger M Gamble,4 Richard Kuntz,6 Shu-Xia Li,4 Danica Marinac-Dabic,7 Frederick A Masoudi,8 Sharon-Lise T Normand,9,10 Isuru Ranasinghe,11 Richard E Shaw,12 Ha...

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Bibliographic Details
Main Authors: Ross JS, Bates J, Parzynski CS, Akar JG, Curtis JP, Desai NR, Freeman JV, Gamble GM, Kuntz R, Li SX, Marinac-Dabic D, Masoudi FA, Normand SLT, Ranasinghe I, Shaw RE, Krumholz HM
Format: Article
Language:English
Published: Dove Medical Press 2017-08-01
Series:Medical Devices : Evidence and Research
Subjects:
implanted cardioverter-defibrillator
methodology
surveillance.
Online Access:https://www.dovepress.com/can-machine-learning-complement-traditional-medical-device-surveillanc-peer-reviewed-article-MDER

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https://www.dovepress.com/can-machine-learning-complement-traditional-medical-device-surveillanc-peer-reviewed-article-MDER

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