Machine Learning Algorithms for Predicting and Risk Profiling of Cardiac Surgery-Associated Acute Kidney Injury

Machine Learning Algorithms for Predicting and Risk Profiling of Cardiac Surgery-Associated Acute Kidney Injury

Using a large national database of cardiac surgical procedures, we applied machine learning (ML) to risk stratification and profiling for cardiac surgery-associated acute kidney injury. We compared performance of ML to established scoring tools. Four ML algorithms were used, including logistic regre...

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Bibliographic Details
Main Authors: Penny-Dimri, J.C., Bergmeir, C., Reid, Christopher, Williams-Spence, J., Cochrane, A.D., Smith, J.A.
Format: Journal Article
Language:English
Published: ELSEVIER INC 2021
Subjects:
Science & Technology
Life Sciences & Biomedicine
Cardiac & Cardiovascular Systems
Cardiovascular System & Cardiology
Artificial intelligence
Machine learning
Emerging technology
Cardiac surgery-associated acute kidney injury
ACUTE-RENAL-FAILURE
ERYTHROPOIETIN
MODELS
Acute Kidney Injury
Algorithms
Cardiac Surgical Procedures
Humans
Logistic Models
Machine Learning
Risk Factors
Online Access:http://purl.org/au-research/grants/nhmrc/1136372
http://hdl.handle.net/20.500.11937/93772

Internet

http://purl.org/au-research/grants/nhmrc/1136372
http://hdl.handle.net/20.500.11937/93772

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