DELINEASI 12 - LEAD SINYAL ELECTROCARDIOGRAM BERBASIS DEEP LEARNING UNTUK PENDETEKSIAN ST ELEVASI

WANDYA, RAMADHANA NOOR SALASSA and Nurmaini, Siti (2024) DELINEASI 12 - LEAD SINYAL ELECTROCARDIOGRAM BERBASIS DEEP LEARNING UNTUK PENDETEKSIAN ST ELEVASI. Undergraduate thesis, Sriwijaya University.

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Abstract

Interpretation of electrocardiogram signal waves is one of the crucial steps to diagnose heart disease. The use of deep learning that has been proven to be able to run feature extraction will be used in this study which aims to facilitate the delineation process of electrocardiogram signal waves. The use of CNN-BiGRU and CNN-BiLSTM architecture to perform delineation on the Lobachevsky University Database (LUDB) datasets shows quite accuracy with F1-score values 94.87% and 94.88%. Delination performed using deep learning model is sufficient to be a reference for ST elevation detection with rule-based method.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	electrocardiogram, deep learning, ST Elevasi, delineasi
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Ramadhana Noor Salassa Wandya
Date Deposited:	16 Oct 2024 05:20
Last Modified:	16 Oct 2024 05:20
URI:	http://repository.unsri.ac.id/id/eprint/158689

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