Cardiac arrest prediction for multivariate time series data have been developed and obtained high precision performance. However, these algorithms still did not achieved high sensitivity and suffer from a high false-alarm. Therefore, we propose a ensemble approach for prediction satisfying precision-recall result compared than other machine learning methods. As a result, our proposed method obtained an overall area under precision-recall curve of 46.7%. It is possible to more accurately respond rapidly cardiac arrest event.
Keywords: Cardiac arrest prediction; ensemble method; soft voting classifier.