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- W2201596913 abstract "We propose a method of arrhythmia detection based on beat morphology, which offers a new set of features for heartbeat classification. This can be performed by nearest-neighbor search, which we applied to heartbeats from the MIT-BIH arrhythmia database. Our classifier achieved an overall accuracy of 98.18% on 103,923 heartbeats." @default.
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- W2201596913 date "2015-11-01" @default.
- W2201596913 modified "2023-09-27" @default.
- W2201596913 title "Heartbeat classification for detecting arrhythmia using normalized beat morphology features" @default.
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- W2201596913 doi "https://doi.org/10.1109/bibm.2015.7359947" @default.
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