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Identifying Ventricular Arrhythmias and Their Predictors by Applying
  Machine Learning Methods to Electronic Health Records in Patients With
  Hypertrophic Cardiomyopathy(HCM-VAr-Risk Model)

Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy(HCM-VAr-Risk Model)

19 September 2021
Moumita Bhattacharya
D. Lu
S. Kudchadkar
Gabriela V. Greenland
P. Lingamaneni
Celia P. Corona-Villalobos
Yufan Guan
J. Marine
J. Olgin
Stefan L. Zimmerman
T. Abraham
H. Shatkay
M. Abraham
ArXiv (abs)PDFHTMLGithub

Papers citing "Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy(HCM-VAr-Risk Model)"

2 / 2 papers shown
CardioForest: An Explainable Ensemble Learning Model for Automatic Wide QRS Complex Tachycardia Diagnosis from ECG
CardioForest: An Explainable Ensemble Learning Model for Automatic Wide QRS Complex Tachycardia Diagnosis from ECGmedRxiv (medRxiv), 2025
Vaskar Chakma
Ju Xiaolin
Heling Cao
Xue Feng
Ji Xiaodong
Pan Haiyan
Gao Zhan
118
1
0
30 Sep 2025
Machine Learning Methods for Identifying Atrial Fibrillation Cases and
  Their Predictors in Patients With Hypertrophic Cardiomyopathy: The
  HCM-AF-Risk Model
Machine Learning Methods for Identifying Atrial Fibrillation Cases and Their Predictors in Patients With Hypertrophic Cardiomyopathy: The HCM-AF-Risk Model
Moumita Bhattacharya
D. Lu
I. Ventoulis
Gabriela V. Greenland
H. Yalçin
...
J. Olgin
Stefan L. Zimmerman
T. Abraham
M. Abraham
H. Shatkay
63
16
0
19 Sep 2021
1
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