Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4966524 | International Journal of Medical Informatics | 2017 | 9 Pages |
Abstract
An ensemble of bagged decision trees was used to classify two groups resulting in a five-fold cross-validation accuracy, specificity, and sensitivity of 98.1%, 100%, and 94.7%, respectively. However, a 20% holdout validation yielded an accuracy, specificity, and sensitivity of 99.5%, 100%, and 98.57%, respectively. Results from this study suggest that features obtained with the combination of PSPR and long-term heart rate variability measures can be used in developing automated CHF diagnosis tools.
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Authors
Ruhi Mahajan, Teeradache Viangteeravat, Oguz Akbilgic,