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 …
[HTML][HTML] Identification and risk stratification of coronary disease by artificial intelligence-enabled ECG
S Awasthi, N Sachdeva, Y Gupta, AG Anto… - …, 2023 - thelancet.com
Background Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of death
worldwide, driven primarily by coronary artery disease (CAD). ASCVD risk estimators such …
worldwide, driven primarily by coronary artery disease (CAD). ASCVD risk estimators such …
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 …
A deep learning algorithm for detecting acute pericarditis by electrocardiogram
(1) Background: Acute pericarditis is often confused with ST-segment elevation myocardial
infarction (STEMI) among patients presenting with acute chest pain in the emergency …
infarction (STEMI) among patients presenting with acute chest pain in the emergency …
[HTML][HTML] Feasibility of Artificial Intelligence–Based Electrocardiography Analysis for the Prediction of Obstructive Coronary Artery Disease in Patients With Stable …
Background: Despite accumulating research on artificial intelligence–based
electrocardiography (ECG) algorithms for predicting acute coronary syndrome (ACS), their …
electrocardiography (ECG) algorithms for predicting acute coronary syndrome (ACS), their …
[HTML][HTML] Artificial Intelligence-Based Early Prediction of Acute Respiratory Failure in the Emergency Department Using Biosignal and Clinical Data
C Han, YJ Jung, JE Park, WY Chung… - Yonsei Medical …, 2024 - pmc.ncbi.nlm.nih.gov
Purpose Early identification of patients at risk for acute respiratory failure (ARF) could help
clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) …
clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) …
[HTML][HTML] An Explainable Artificial Intelligence-enabled ECG Framework for the Prediction of Subclinical Coronary Atherosclerosis
Coronary artery calcium (CAC) as assessed by computed tomography (CT) is a marker of
subclinical coronary atherosclerosis. However, routine application of CAC scoring via CT is …
subclinical coronary atherosclerosis. However, routine application of CAC scoring via CT is …
Machine Learning Methods For Classification of Individuals With Coronary Artery Calcification
Coronary artery calcification (CAC) due to coronary artery disease (CAD) poses significant
risks of heart attack, sudden cardiac death, and other cardiac complications. CAC reflects …
risks of heart attack, sudden cardiac death, and other cardiac complications. CAC reflects …
Introduction to AI-driven diagnostics and human–machine interfaces
Introduction to AI-driven diagnostics and human–machine interfaces - Book chapter -
IOPscience Skip to content IOP Science home Accessibility Help Search all IOPscience …
IOPscience Skip to content IOP Science home Accessibility Help Search all IOPscience …
Identification of Differentially Expressed Genes and Prediction of Expression Regulation Networks in Dysfunctional Endothelium
F Cheng, Y Zeng, M Zhao, Y Zhu, J Li, R Tang - Genes, 2022 - mdpi.com
The detection of early coronary atherosclerosis (ECA) is still a challenge and the mechanism
of endothelial dysfunction remains unclear. In the present study, we aimed to identify …
of endothelial dysfunction remains unclear. In the present study, we aimed to identify …