Název:
Multiple Instance Learning Framework Used For Ecg Premature Contraction Localization
Autoři:
Novotna, Petra Typ dokumentu: Příspěvky z konference
Jazyk:
eng
Nakladatel: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstrakt:
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).
Klíčová slova:
arrhytmia; CNN; ECG; EEICT; localization; MIL; PAC; PVC Zdrojový dokument: Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers, ISBN 978-80-214-5942-7
Instituce: Vysoké učení technické v Brně
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Informace o dostupnosti dokumentu:
Plný text je dostupný v Digitální knihovně VUT. Původní záznam: http://hdl.handle.net/11012/200770