Systematic reviews of machine learning in healthcare: a literature review
K Kolasa, B Admassu… - Expert Review of …, 2024 - Taylor & Francis
Introduction The increasing availability of data and computing power has made machine
learning (ML) a viable approach to faster, more efficient healthcare delivery. Methods A …
learning (ML) a viable approach to faster, more efficient healthcare delivery. Methods A …
Deep Generative Models for Physiological Signals: A Systematic Literature Review
In this paper, we present a systematic literature review on deep generative models for
physiological signals, particularly electrocardiogram, electroencephalogram …
physiological signals, particularly electrocardiogram, electroencephalogram …
[HTML][HTML] A deep learning technique for biometric authentication using ECG beat template matching
An electrocardiogram (ECG) is a unique representation of a person's identity, similar to
fingerprints, and its rhythm and shape are completely different from person to person …
fingerprints, and its rhythm and shape are completely different from person to person …
Artificial intelligence based approach for categorization of COVID-19 ECG images in presence of other cardiovascular disorders
Abstract Coronavirus disease (COVID-19) is a class of SARS-CoV-2 virus which is initially
identified in the later half of the year 2019 and then evolved as a pandemic. If it is not …
identified in the later half of the year 2019 and then evolved as a pandemic. If it is not …
[HTML][HTML] ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis
C García-Vicente, GC Gutiérrez-Tobal… - Computers in Biology …, 2023 - Elsevier
Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is
characterized by partial or complete obstruction of the upper airway during sleep. The …
characterized by partial or complete obstruction of the upper airway during sleep. The …
[HTML][HTML] Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences
To develop diagnostic imaging approaches, this paper emphasizes the transformational
potential of merging geophysics with health sciences. Diagnostic imaging technology …
potential of merging geophysics with health sciences. Diagnostic imaging technology …
ECGencode: Compact and computationally efficient deep learning feature encoder for ECG signals
L Bontinck, K Fonteyn, T Dhaene… - Expert Systems with …, 2024 - Elsevier
The visual interpretation of electrocardiogram (ECG) data is driven by human pattern
recognition and requires in-depth medical knowledge. Although state-of-the-art deep …
recognition and requires in-depth medical knowledge. Although state-of-the-art deep …
3DECG-Net: ECG fusion network for multi-label cardiac arrhythmia detection
Cardiovascular diseases represent the leading global cause of death, typically diagnosed
and addressed through electrocardiograms (ECG), which record the heart's electrical …
and addressed through electrocardiograms (ECG), which record the heart's electrical …
ECG-based data-driven solutions for diagnosis and prognosis of cardiovascular diseases: A systematic review
Cardiovascular diseases (CVD) are a leading cause of death globally, and result in
significant morbidity and reduced quality of life. The electrocardiogram (ECG) plays a crucial …
significant morbidity and reduced quality of life. The electrocardiogram (ECG) plays a crucial …
[HTML][HTML] Enhancing trustworthy deep learning for image classification against evasion attacks: a systematic literature review
In the rapidly evolving field of Deep Learning (DL), the trustworthiness of models is essential
for their effective application in critical domains like healthcare and autonomous systems …
for their effective application in critical domains like healthcare and autonomous systems …