Semi-supervised learning of probabilistic models for ECG segmentation.
We present a novel semi-supervised learning algorithm, based upon the EM algorithm for maximum likelihood estimation, which can be used to learn probabilistic models from subjectively labelled data. We demonstrate the method on the task of automated ECG segmentation, with a particular emphasis on th...
Main Authors: | Hughes, N, Roberts, S, Tarassenko, L |
---|---|
格式: | Journal article |
语言: | English |
出版: |
2004
|
相似书籍
-
Exploring probabilistic models for semi-supervised learning
由: Wang, J
出版: (2023) -
Markov models for automated ECG interval analysis
由: Hughes, N, et al.
出版: (2004) -
Probabilistic models for multi-view semi-supervised learning and coding
由: Christoudias, C. Mario (Christos Mario)
出版: (2010) -
Semi-supervised active transfer learning for fetal ECG arrhythmia detection
由: Mohammad Reza Mohebbian, et al.
出版: (2023-01-01) -
Supervised ECG wave segmentation using convolutional LSTM
由: Aman Malali, et al.
出版: (2020-09-01)