Identifying Predictors of Heart Failure Readmission in Patients From a Statutory Health Insurance Da...
Identifying Predictors of Heart Failure Readmission in Patients From a Statutory Health Insurance Database: Retrospective Machine Learning Study
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Publisher
Canada: JMIR Publications
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Language
English
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Publisher
Canada: JMIR Publications
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Contents
Patients with heart failure (HF) are the most commonly readmitted group of adult patients in Germany. Most patients with HF are readmitted for noncardiovascular reasons. Understanding the relevance of HF management outside the hospital setting is critical to understanding HF and factors that lead to readmission. Application of machine learning (ML)...
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Full title
Identifying Predictors of Heart Failure Readmission in Patients From a Statutory Health Insurance Database: Retrospective Machine Learning Study
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TN_cdi_doaj_primary_oai_doaj_org_article_4e41f75bc04a4625b86a2d3ce0e49ca2
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_4e41f75bc04a4625b86a2d3ce0e49ca2
Other Identifiers
ISSN
2561-1011
E-ISSN
2561-1011
DOI
10.2196/54994
