Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study

BACKGROUND: The current acute kidney injury (AKI) risk prediction model for patients undergoing percutaneous coronary intervention (PCI) from the American College of Cardiology (ACC) National Cardiovascular Data Registry (NCDR) employed regression techniques. This study aimed to evaluate whether mod...

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Bibliographic Details
Published in:PLoS Med
Main Authors: Huang, Chenxi, Murugiah, Karthik, Mahajan, Shiwani, Li, Shu-Xia, Dhruva, Sanket S., Haimovich, Julian S., Wang, Yongfei, Schulz, Wade L., Testani, Jeffrey M., Wilson, Francis P., Mena, Carlos I., Masoudi, Frederick A., Rumsfeld, John S., Spertus, John A., Mortazavi, Bobak J., Krumholz, Harlan M.
Format: Artigo
Language:Inglês
Published: Public Library of Science 2018
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Research Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC6258473/
https://ncbi.nlm.nih.gov/pubmed/30481186
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pmed.1002703
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