Developing an Agnostic Risk Prediction Model for Early AKI Detection in Cancer Patients

Developing an Agnostic Risk Prediction Model for Early AKI Detection in Cancer Patients

Acute kidney injury (AKI) is a common complication among oncology patients associated with lower remission rates and higher mortality. To reduce the impact of this condition, we aimed to predict AKI earlier than existing tools, to allow clinical intervention before occurrence. We trained a random fo...

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Bibliographic Details
Main Authors: Lauren A. Scanlon, Catherine O’Hara, Alexander Garbett, Matthew Barker-Hewitt, Jorge Barriuso
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Cancers
Subjects:
acute kidney injury
artificial intelligence
clinical decision making
early diagnosis
hematologic tests
machine learning
Online Access:https://www.mdpi.com/2072-6694/13/16/4182

Internet

https://www.mdpi.com/2072-6694/13/16/4182

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