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

BACKGROUND: Machine learning methods may complement traditional analytic methods for medical device surveillance. METHODS AND RESULTS: Using data from the National Cardiovascular Data Registry for implantable cardioverter–defibrillators (ICDs) linked to Medicare administrative claims for longitudina...

Descripción completa

Detalles Bibliográficos
Autores principales: Ross, Joseph S, Bates, Jonathan, Parzynski, Craig S, Akar, Joseph G, Curtis, Jeptha P, Desai, Nihar R, Freeman, James V, Gamble, Ginger M, Kuntz, Richard, Li, Shu-Xia, Marinac-Dabic, Danica, Masoudi, Frederick A, Normand, Sharon-Lise T, Ranasinghe, Isuru, Shaw, Richard E, Krumholz, Harlan M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2017
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566316/
https://www.ncbi.nlm.nih.gov/pubmed/28860874
http://dx.doi.org/10.2147/MDER.S138158

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566316/
https://www.ncbi.nlm.nih.gov/pubmed/28860874
http://dx.doi.org/10.2147/MDER.S138158

Ejemplares similares