Applications of machine learning methods in kidney disease: hope or hype?

Journal: Current opinion in nephrology and hypertension

Published Date: May 1, 2020

Abstract

PURPOSE OF REVIEW: The universal adoption of electronic health records, improvement in technology, and the availability of continuous monitoring has generated large quantities of healthcare data. Machine learning is increasingly adopted by nephrology researchers to analyze this data in order to improve the care of their patients.

Authors

Lili Chan

Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, USA.
Akhil Vaid

Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY 10029 USA.
Girish N Nadkarni

Division of Data-Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Keywords

Algorithms Humans Kidney Diseases Machine Learning Natural Language Processing Translational Research, Biomedical

External Resources

View on PubMed Access via DOI PubMed (32235273)

Applications of machine learning methods in kidney disease: hope or hype?

Abstract

Authors

Keywords

External Resources

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