A stacking-based model for predicting 30-day all-cause hospital readmissions of patients with acute myocardial infarction

A stacking-based model for predicting 30-day all-cause hospital readmissions of patients with acute myocardial infarction

Abstract Background Acute myocardial infarction (AMI) is a serious cardiovascular disease, followed by a high readmission rate within 30-days of discharge. Accurate prediction of AMI readmission is a crucial way to identify the high-risk group and optimize the distribution of medical resources. Meth...

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Bibliographic Details
Main Authors: Zhen Zhang, Hang Qiu, Weihao Li, Yucheng Chen
Format: Article
Language:English
Published: BMC 2020-12-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Acute myocardial infarction
Hospital readmission
Clinical data
Machine learning
Self-adaptive
Stacking-based model learning
Online Access:https://doi.org/10.1186/s12911-020-01358-w

Internet

https://doi.org/10.1186/s12911-020-01358-w

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