Artificial intelligence in disease diagnostics: A critical review and classification on the current state of research guiding future direction

M Mirbabaie, S Stieglitz, NRJ Frick - Health and Technology, 2021 - Springer
The diagnosis of diseases is decisive for planning proper treatment and ensuring the well-
being of patients. Human error hinders accurate diagnostics, as interpreting medical …

Ecg heartbeat classification: A deep transferable representation

M Kachuee, S Fazeli… - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
Electrocardiogram (ECG) can be reliably used as a measure to monitor the functionality of
the cardiovascular system. Recently, there has been a great attention towards accurate …

ECG heartbeat classification using multimodal fusion

Z Ahmad, A Tabassum, L Guan, NM Khan - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) is an authoritative source to diagnose and counter critical
cardiovascular syndromes such as arrhythmia and myocardial infarction (MI). Current …

Detecting and interpreting myocardial infarction using fully convolutional neural networks

N Strodthoff, C Strodthoff - Physiological measurement, 2019 - iopscience.iop.org
Objective: We aim to provide an algorithm for the detection of myocardial infarction that
operates directly on ECG data without any preprocessing and to investigate its decision …

Artificial neural networks in medicine

JM Haglin, G Jimenez, AEM Eltorai - Health and Technology, 2019 - Springer
In the past several decades, the intricate neural networks of the human brain have inspired
the further development of intelligent systems. Many disciplines, including the complex field …

A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation

SW Smith, B Walsh, K Grauer, K Wang, J Rapin… - Journal of …, 2019 - Elsevier
Background Cardiologs® has developed the first electrocardiogram (ECG) algorithm that
uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and …

MyWear: A novel smart garment for automatic continuous vital monitoring

SC Sethuraman, P Kompally… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Wearables are getting large acceptance in the continuous monitoring of health status and
physiological data. Medical devices and their connectivity through Internet along with the …

Electrocardiogram heartbeat classification for arrhythmias and myocardial infarction

BT Pham, PT Le, TC Tai, YC Hsu, YH Li, JC Wang - Sensors, 2023 - mdpi.com
An electrocardiogram (ECG) is a basic and quick test for evaluating cardiac disorders and is
crucial for remote patient monitoring equipment. An accurate ECG signal classification is …

Ecg heart-beat classification using multimodal image fusion

Z Ahmad, A Tabassum, L Guan… - ICASSP 2021-2021 IEEE …, 2021 - ieeexplore.ieee.org
In this paper, we present a novel Image Fusion Model (IFM) for ECG heart-beat classification
to overcome the weaknesses of existing machine learning techniques that rely either on …

Deep learning for cardiologist-level myocardial infarction detection in electrocardiograms

A Gupta, E Huerta, Z Zhao, I Moussa - … of the EMBEC 2020, November 29 …, 2021 - Springer
Myocardial infarction is the leading cause of death worldwide. In this paper, we design
domain-inspired neural network models to detect myocardial infarction. First, we study the …