A clinical, proteomics, and artificial intelligence‐driven model to predict acute kidney injury in p...
A clinical, proteomics, and artificial intelligence‐driven model to predict acute kidney injury in patients undergoing coronary angiography
About this item
Full title
Author / Creator
Publisher
New York: Wiley Periodicals, Inc
Journal title
Language
English
Formats
Publication information
Publisher
New York: Wiley Periodicals, Inc
Subjects
More information
Scope and Contents
Contents
Background
Standard measures of kidney function are only modestly useful for accurate prediction of risk for acute kidney injury (AKI).
Hypothesis
Clinical and biomarker data can predict AKI more accurately.
Methods
Using Luminex xMAP technology, we measured 109 biomarkers in blood from 889 patients prior to undergoing coronary angio...
Alternative Titles
Full title
A clinical, proteomics, and artificial intelligence‐driven model to predict acute kidney injury in patients undergoing coronary angiography
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6712314
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6712314
Other Identifiers
ISSN
0160-9289
E-ISSN
1932-8737
DOI
10.1002/clc.23143
