Similarity : Deep learning with a recurrent network structure in the sequence modeling of imbalanced data for ECG-Rhythm Classifier

Sukemi, Sukemi and DARMAWAHYUNI, ANNISA (2023) Similarity : Deep learning with a recurrent network structure in the sequence modeling of imbalanced data for ECG-Rhythm Classifier. Perpustakaan UNSRI.

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Abstract

The interpretation of Myocardial infarction (MI) via electrodiagram (ECG) signal is a challenging tas. ECg signals'mhorpological view show significant variaton in different patients under different physical conditions. several..... Apparently, deep learning with the LSTM technque is a potential method for classifying sequential data that implements time steps in the ECG signal.

Item Type:	Other
Subjects:	#3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Dr. Sukemi Sukemi
Date Deposited:	29 Apr 2023 04:58
Last Modified:	29 Apr 2023 04:58
URI:	http://repository.unsri.ac.id/id/eprint/98116

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