Journal of medical engineering & technology
Apr 16, 2024
Sleep apnoea is a common disorder affecting sleep quality by obstructing the respiratory airway. This disorder can also be correlated to certain diseases like stroke, depression, neurocognitive disorder, non-communicable disease, etc. We implemented ...
ECG classification or heartbeat classification is an extremely valuable tool in cardiology. Deep learning-based techniques for the analysis of ECG signals assist human experts in the timely diagnosis of cardiac diseases and help save precious lives. ...
AIM: To develop and employ machine learning (ML) algorithms to analyse electrocardiograms (ECGs) for the diagnosis of cardiac autonomic neuropathy (CAN).
Computer methods and programs in biomedicine
Apr 9, 2024
BACKGROUND AND OBJECTIVE: Current automatic electrocardiogram (ECG) diagnostic systems could provide classification outcomes but often lack explanations for these results. This limitation hampers their application in clinical diagnoses. Previous supe...
Biological age may be a more valuable predictor of morbidity and mortality than a person's chronological age. Mathematical models have been used for decades to predict biological age, but recent developments in artificial intelligence (AI) have led t...
Pacing and clinical electrophysiology : PACE
Apr 7, 2024
BACKGROUND: Left bundle branch block (LBBB) induced cardiomyopathy is an increasingly recognized disease entity. However, no clinical testing has been shown to be able to predict such an occurrence.
Myocardial infarction (MI) is a common cardiovascular disease caused by the blockages of coronary arteries. The visual inspection of electrocardiogram (ECG) is the main diagnosis pattern, while it is taxing and time-consuming. Motivated from state re...
BACKGROUND: Convolutional neural networks (CNNs) have emerged as a novel method for evaluating heart failure (HF) in adult electrocardiograms (ECGs). However, such CNNs are not applicable to pediatric HF, where abnormal anatomy of congenital heart de...
BACKGROUND: Predicting long-term mortality postkidney transplantation (KT) using baseline clinical data presents significant challenges. This study aims to evaluate the predictive power of artificial intelligence (AI)-enabled analysis of preoperative...
The efficacy of convolutional neural network (CNN)-enhanced electrocardiography (ECG) in detecting hypertrophic cardiomyopathy (HCM) and dilated HCM (dHCM) remains uncertain in real-world applications. This retrospective study analyzed data from 19,1...