[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review

G Petmezas, L Stefanopoulos, V Kilintzis… - JMIR medical …, 2022 - medinform.jmir.org
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 …

[HTML][HTML] Successes and challenges of artificial intelligence in cardiology

B Vandenberk, DS Chew, D Prasana, S Gupta… - Frontiers in Digital …, 2023 - frontiersin.org
In the past decades there has been a substantial evolution in data management and data
processing techniques. New data architectures made analysis of big data feasible …

Implications of the use of artificial intelligence predictive models in health care settings: A simulation study

A Vaid, A Sawant, M Suarez-Farinas, J Lee… - Annals of Internal …, 2023 - acpjournals.org
Background: Substantial effort has been directed toward demonstrating uses of predictive
models in health care. However, implementation of these models into clinical practice may …

A foundational vision transformer improves diagnostic performance for electrocardiograms

A Vaid, J Jiang, A Sawant, S Lerakis, E Argulian… - NPJ Digital …, 2023 - nature.com
The electrocardiogram (ECG) is a ubiquitous diagnostic modality. Convolutional neural
networks (CNNs) applied towards ECG analysis require large sample sizes, and transfer …

Detection of left ventricular systolic dysfunction from electrocardiographic images

V Sangha, AA Nargesi, LS Dhingra, A Khunte… - Circulation, 2023 - Am Heart Assoc
BACKGROUND: Left ventricular (LV) systolic dysfunction is associated with a> 8-fold
increased risk of heart failure and a 2-fold risk of premature death. The use of ECG signals in …

The use of artificial intelligence for delivery of essential health services across WHO regions: a scoping review

JC Okeibunor, A Jaca, CJ Iwu-Jaja… - Frontiers in Public …, 2023 - frontiersin.org
Background Artificial intelligence (AI) is a broad outlet of computer science aimed at
constructing machines capable of simulating and performing tasks usually done by human …

Heart failure diagnosis in the general community–Who, how and when? A clinical consensus statement of the Heart Failure Association (HFA) of the European Society …

KF Docherty, CSP Lam, A Rakisheva… - European Journal of …, 2023 - Wiley Online Library
A significant proportion of patients experience delays in the diagnosis of heart failure due to
the non‐specific signs and symptoms of the syndrome. Diagnostic tools such as …

Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives

X Sun, Y Yin, Q Yang, T Huo - European Journal of Medical Research, 2023 - Springer
Artificial intelligence (AI), the technique of extracting information from complex database
using sophisticated computer algorithms, has incorporated itself in medical field. AI …

Deep learning for echocardiography: introduction for clinicians and future vision: State-of-the-Art Review

C Krittanawong, AMS Omar, S Narula, PP Sengupta… - Life, 2023 - mdpi.com
Exponential growth in data storage and computational power is rapidly narrowing the gap
between translating findings from advanced clinical informatics into cardiovascular clinical …

Artificial intelligence-enabled electrocardiography predicts left ventricular dysfunction and future cardiovascular outcomes: a retrospective analysis

HY Chen, CS Lin, WH Fang, YS Lou… - Journal of Personalized …, 2022 - mdpi.com
BACKGROUND: The ejection fraction (EF) provides critical information about heart failure
(HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for …