Multiple Instance Learning Framework Used For Ecg Premature Contraction Localization
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We propose the model combining convolutional neural network with multiple instancelearning in order to localize the premature atrial contraction and premature ventricular contraction.The model is based on ResNet architecture modified for 1D signal processing. Model was trainedon China Physiological Signal Challenge 2018 database extended by manually labeled ground truthpositions of premature complexes. The presented method did not reach satisfying results in PAClocalization (with dice = 0.127 for avg-pooling implementation). On the other hand, results of localizationof PVCs were comparable with other published studies (with dice = 0.952 for avg-poolingimplementation).
Document typePeer reviewed
Document versionFinal PDF
SourceProceedings I of the 27st Conference STUDENT EEICT 2021: General papers. s. 311-315. ISBN 978-80-214-5942-7
- Student EEICT 2021