Neural Network Architectures Comparison for Atrial Fibrillation Detection

被引：0

作者：

Aguilar, Jaylenne ^{[1
]}

Tacuri-Pizha, Nelly ^{[1
]}

Cevallos-Bermeo, Gabriela ^{[1
]}

Villalba-Meneses, Fernando ^{[1
]}

Cruz-Varela, Jonathan ^{[1
]}

Teran-Grijalva, Cristhian ^{[2
]}

Cadena-Morejon, Carolina ^{[3
]}

Tirado-Espin, Andres ^{[3
,4
]}

Almeida-Galarraga, Diego ^{[1
,4
]}

机构：

[1] Univ Yachay Tech, Sch Biol Sci & Engn, Urcuqui, Ecuador

[2] Ejercito Ecuatoriano, Grp Fuerzas Especiales Grad Miguel Iturralde 27, Latacunga, Ecuador

[3] Univ Yachay Tech, Sch Math & Computat Sci, Urcuqui, Ecuador

[4] Univ Otavalo, Otavalo, Ecuador

来源：

2023 FOURTH INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND SOFTWARE TECHNOLOGIES, ICI2ST 2023 | 2023年

关键词：

Atrial fibrillation detection; AT' diagnosis; AF detection with AIL; CLASSIFICATION;

D O I：

10.1109/ICI2ST62251.2023.00009

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Atrial fibrillation (AF) is the most common cardiac arrhythmia affecting about 50,000 new people each year in Latin America. At' is characterized by irregular and rapid heartbeats that can lead to serious complications, such as stroke, heart failure, and all-cause mortality. Traditional methods for AF detection are time consuming and can be prone to human error. Therefore, this work reports the results from two methods using machine learning techniques to assist the diagnosis of Al' through 2 hybrid models of neural networks: The ID- CNN with BILSTN1 model and the NlobileNetV2 with BILSTM model which reached 81 and 75% accuracy respectively.

引用

页码：9 / 15

页数：7

共 50 条

[21] MGNN: A multiscale grouped convolutional neural network for efficient atrial fibrillation detection
Liu, Sen
Wang, Aiguo
Deng, Xintao
Yang, Cuiwei
[J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2022, 148
[22] Detection of Atrial Fibrillation based on Synchronized Beats Image with Lightweight Neural Network
Thway, Khaing Su
Somboon, Pakpum
Teeramongkonrasmee, Arporn
[J]. 2022 37TH INTERNATIONAL TECHNICAL CONFERENCE ON CIRCUITS/SYSTEMS, COMPUTERS AND COMMUNICATIONS (ITC-CSCC 2022), 2022, : 341 - 344
[23] DAAT: A New Method to Train Convolutional Neural Network on Atrial Fibrillation Detection
Zhang, Jian
Liu, Juan
Li, Pei-Fang
Feng, Jing
[J]. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, 12465 LNAI : 280 - 290
[24] Detection of Brief Episodes of Atrial Fibrillation Based on Electrocardiomatrix and Convolutional Neural Network
Salinas-Martinez, Ricardo
de Bie, Johannes
Marzocchi, Nicoletta
Sandberg, Frida
[J]. FRONTIERS IN PHYSIOLOGY, 2021, 12
[25] Quantifying deep neural network uncertainty for atrial fibrillation detection with limited labels
Brian Chen
Golara Javadi
Alexander Hamilton
Stephanie Sibley
Philip Laird
Purang Abolmaesumi
David Maslove
Parvin Mousavi
[J]. Scientific Reports, 12
[26] A NEURAL-NETWORK SYSTEM FOR DETECTION OF ATRIAL-FIBRILLATION IN AMBULATORY ELECTROCARDIOGRAMS
CUBANSKI, D
CYGANSKI, D
ANTMAN, EM
FELDMAN, CL
[J]. JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, 1994, 5 (07) : 602 - 608
[27] Comparison of Deep Neural Network Architectures for Fault Detection in Tennessee Eastman Process
Chadha, Gavneet Singh
Schwung, Andreas
[J]. 2017 22ND IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2017,
[28] Neural Network Approach for T-wave End Detection: A Comparison of Architectures
Suarez Leon, Alexander A.
Matos Molina, Danelia
Vazquez Seisdedos, Carlos R.
Goovaerts, Griet
Vandeput, Steven
Van Huffel, Sabine
[J]. 2015 COMPUTING IN CARDIOLOGY CONFERENCE (CINC), 2015, 42 : 589 - 592
[29] Robust ECG Signal Classification for Detection of Atrial Fibrillation Using a Novel Neural Network
Xiong, Zhaohan
Stiles, Martin K.
Zhao, Jichao
[J]. 2017 COMPUTING IN CARDIOLOGY (CINC), 2017, 44
[30] Neural Network Detection of Atrial Fibrillation by Lorenz Plot Images of Interbeat Interval Variation
Kisohara, Masaya
Masuda, Yuto
Yuda, Emi
Hayano, Junichiro
[J]. 2018 IEEE 7TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE 2018), 2018, : 244 - 245

← 1 2 3 4 5 →