[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
Clinical applications, methodology, and scientific reporting of electrocardiogram deep-learning models: A systematic review
Background The electrocardiogram (ECG) is one of the most common diagnostic tools
available to assess cardiovascular health. The advent of advanced computational …
available to assess cardiovascular health. The advent of advanced computational …
Deep learning electrocardiographic analysis for detection of left-sided valvular heart disease
P Elias, TJ Poterucha, V Rajaram, LM Moller… - Journal of the American …, 2022 - jacc.org
Background Valvular heart disease is an important contributor to cardiovascular morbidity
and mortality and remains underdiagnosed. Deep learning analysis of electrocardiography …
and mortality and remains underdiagnosed. Deep learning analysis of electrocardiography …
Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review
HV Denysyuk, RJ Pinto, PM Silva, RP Duarte… - Heliyon, 2023 - cell.com
The prevalence of cardiovascular diseases is increasing around the world. However, the
technology is evolving and can be monitored with low-cost sensors anywhere at any time …
technology is evolving and can be monitored with low-cost sensors anywhere at any time …
A review of evaluation approaches for explainable AI with applications in cardiology
Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI
models and is important in building trust in model predictions. XAI explanations themselves …
models and is important in building trust in model predictions. XAI explanations themselves …
Meta-analysis of the performance of AI-driven ECG interpretation in the diagnosis of valvular heart diseases
Valvular heart diseases (VHDs) significantly impact morbidity and mortality rates worldwide.
Early diagnosis improves patient outcomes. Artificial intelligence (AI) applied to …
Early diagnosis improves patient outcomes. Artificial intelligence (AI) applied to …
Automatic detection of left ventricular dilatation and hypertrophy from electrocardiograms using deep learning
T Kokubo, S Kodera, S Sawano… - International Heart …, 2022 - jstage.jst.go.jp
Left ventricular dilatation (LVD) and left ventricular hypertrophy (LVH) are risk factors for
heart failure, and their detection improves heart failure screening. This study aimed to …
heart failure, and their detection improves heart failure screening. This study aimed to …
Prospects for cardiovascular medicine using artificial intelligence
As the importance of artificial intelligence (AI) in the clinical setting increases, the need for
clinicians to understand AI is also increasing. This review focuses on the fundamental …
clinicians to understand AI is also increasing. This review focuses on the fundamental …
Applying masked autoencoder-based self-supervised learning for high-capability vision transformers of electrocardiographies
S Sawano, S Kodera, N Setoguchi, K Tanabe… - Plos one, 2024 - journals.plos.org
The generalization of deep neural network algorithms to a broader population is an
important challenge in the medical field. We aimed to apply self-supervised learning using …
important challenge in the medical field. We aimed to apply self-supervised learning using …
[HTML][HTML] The emerging roles of machine learning in cardiovascular diseases: A narrative review
L Chen, Z Han, J Wang, C Yang - Annals of Translational Medicine, 2022 - ncbi.nlm.nih.gov
Methods This study searched relevant literature published in National Center for
Biotechnology Information (NCBI) PubMed from 2016 to 2022. The relevant literature was …
Biotechnology Information (NCBI) PubMed from 2016 to 2022. The relevant literature was …