Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Ele...
Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy(HCM-VAr-Risk Model)
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index of 0.69), which utilize a few clinical variables. We assessed whether data-driven machine learning me...
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Full title
Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy(HCM-VAr-Risk Model)
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TN_cdi_proquest_journals_2574962082
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2574962082
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2109.09210
