The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model.

Journal: Critical care medicine

PMID: 29596073

Abstract

OBJECTIVES: To develop an acute kidney injury risk prediction model using electronic health record data for longitudinal use in hospitalized patients.

Authors

Jay L Koyner

Section of Nephrology, Department of Medicine, University of Chicago, Chicago, Illinois.
Kyle A Carey

Department of Medicine, University of Chicago, Chicago IL, United States.
Dana P Edelson
Matthew M Churpek

Department of Medicine, University of Wisconsin-Madison, Madison, WI, United States.

Keywords

Acute Kidney Injury Algorithms Area Under Curve Creatinine Electronic Health Records Female Humans Machine Learning Male Middle Aged Models, Statistical Renal Replacement Therapy Reproducibility of Results ROC Curve

External Resources

View on PubMed Access via DOI PubMed (29596073)

The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model.

Abstract

Authors

Keywords

External Resources

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