Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study

Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study

Abstract Backgrounds We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care. Methods Data from the UK Sentinel Stroke National Audit Program between 2013 to 2019 wer...

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Bibliographic Details
Main Authors: Wenjuan Wang, Anthony G. Rudd, Yanzhong Wang, Vasa Curcin, Charles D. Wolfe, Niels Peek, Benjamin Bray
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Neurology
Subjects:
Stroke
Machine learning
Statistical analysis
Risk prediction
30-day mortality
Outcomes
Online Access:https://doi.org/10.1186/s12883-022-02722-1

Internet

https://doi.org/10.1186/s12883-022-02722-1

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