Myocardial Infarction

Heart Rate and its Variability From Short-Term ECG Recordings as Potential Biomarkers for Detecting Mild Cognitive Impairment.

Alterations in Heart Rate (HR) and Heart Rate Variability (HRV) reflect autonomic dysfunction associated with neurodegeneration making them biomarkers suitable for detecting Mild Cognitive Impairment (MCI). The study involves 297 urban Indian participants [48.48% (144) were male and 51.51% (153) were female]. MCI was detected in 19.19% (57) of participants and the rest, 80.8% (240) of them were ...

Assessment of Osteoprotegerin and Receptor Activator of Nf-Κb Ligand in Malaysian Male Patients with Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Background: Limited information exists regarding the pathophysiological interactions between osteoporosis and chronic obstructive pulmonary disease (COPD). Objective: To study the association of Osteoprotegerin (OPG) and receptor activator of nuclear factor kappa-Β ligand (RANKL) in male COPD patients. Methods: An observational clinical study was conducted at Penang General Hospital in Malaysia. P...

Improved diagnostic performance of insertable cardiac monitors by an artificial intelligence-based algorithm.

AIMS: The increasing use of insertable cardiac monitors (ICM) produces a high rate of false positive (FP) diagnoses. Their verification results in a h...

[Advances in chest imaging in early chronic obstructive pulmonary disease].

Chronic obstructive pulmonary disease(COPD)is a heterogeneous and complex disease, and is characterized by exertional dyspnea and chronic cough. For m...

Deep learning-derived 12-lead electrocardiogram-based genotype prediction for hypertrophic cardiomyopathy: a pilot study.

Given the psychosocial and ethical burden, patients with hypertrophic cardiomyopathy (HCMs) could benefit from the establishment of genetic probabili...

Changes of plasma Rap1A levels in patients with in-stent restenosis after percutaneous coronary intervention and the underlying mechanisms.

OBJECTIVES: Percutaneous coronary intervention (PCI) is one of the most important treatments for coronary artery disease (CAD). However, in-stent rest...

Deep Learning-based Prediction of Percutaneous Recanalization in Chronic Total Occlusion Using Coronary CT Angiography.

UNLABELLED: Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO), but manual prediction scores of percutaneous c...

[Saved myocardium in acute ST-segment elevation myocardial infarction post-reperfusion: Analysis by cardiac magnetic resonance].

OBJECTIVE: To quantify by cardiovascular magnetic resonance the salvaged myocardium in the myocardium supplied by the infarct-related artery in reperf...

Assessing the Generalizability of a Deep Learning-based Automated Atrial Fibrillation Algorithm.

Automated detection of atrial fibrillation (AF) from electrocardiogram (ECG) traces remains a challenging task and is crucial for telemonitoring of pa...

Gated CNN-Transformer Network for Automatic Cardiovascular Diagnosis using 12-lead Electrocardiogram.

12-lead electrocardiogram (ECG) is a widely used method in the diagnosis of cardiovascular disease (CVD). With the increase in the number of CVD patie...

Classification of Continuous ECG Segments - Performance Analysis of a Deep Learning Model.

Classification of electrocardiogram (ECG) signals plays an important role in the diagnosis of heart diseases. It is a complex and non-linear signal, w...

Deep Learning-Based Predictive Model for Revascularization of Chronic Total Occlusions on Angiographic Imaging.

Revascularization of chronic total occlusions (CTO) is currently one of the most complex procedures in percutaneous coronary intervention (PCI), requi...

Impact of synthetic noise signature and physiologic ECG signal on designing ML-based ECG noise detection framework.

Automatic signal analysis using artificial intelligence is getting popular in digital healthcare, such as ECG rhythm analysis, where ECG signals are c...

Assessment of Driver's Stress using Multimodal Biosignals and Regularized Deep Kernel Learning.

In this work, we classify the stress state of car drivers using multimodal physiological signals and regularized deep kernel learning. Using a driving...

High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI.

Real-time cine cardiac MRI provides an ECG-free free-breathing alternative to clinical gold-standard ECG-gated breath-hold segmented cine MRI for eval...

Beatwise ECG Classification for the Detection of Atrial Fibrillation with Deep Learning.

Atrial fibrillation (AF) is the most common, sustained cardiac arrhythmia. Early intervention and treatment could have a much higher chance of reversi...

Memory Classifiers for Robust ECG Classification against Physiological Noise.

The development of sophisticated machine learning algorithms has made it possible to detect critical health conditions like cardiac arrhythmia, direct...

QTNet: Deep Learning for Estimating QT Intervals Using a Single Lead ECG.

QT prolongation often leads to fatal arrhythmia and sudden cardiac death. Antiarrhythmic drugs can increase the risk of QT prolongation and therefore ...

Data Quality in Healthcare for the Purpose of Artificial Intelligence: A Case Study on ECG Digitalization.

The quantity of data generated within healthcare is increasing exponentially. Following this development, the interest of using data driven methodolog...

The Necessity of Multiple Data Sources for ECG-Based Machine Learning Models.

Even though the interest in machine learning studies is growing significantly, especially in medicine, the imbalance between study results and clinica...