An Algorithm Based on Deep Learning for Predicting In‐Hospital Cardiac Arrest
Background In‐hospital cardiac arrest is a major burden to public health, which affects patient safety. Although traditional track‐and‐trigger systems are used to predict cardiac arrest early, they have limitations, with low sensitivity and high false‐alarm rates. We propose a deep learning–based ea...
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| Hauptverfasser: | , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Wiley
2018-07-01
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| Schriftenreihe: | Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease |
| Schlagworte: | |
| Online-Zugang: | https://www.ahajournals.org/doi/10.1161/JAHA.118.008678 |
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