AIMC Topic: Electrocardiography

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Detection of hypertrophic cardiomyopathy by an artificial intelligence electrocardiogram in children and adolescents.

International journal of cardiology
BACKGROUND: There is no established screening approach for hypertrophic cardiomyopathy (HCM). We recently developed an artificial intelligence (AI) model for the detection of HCM based on the 12‑lead electrocardiogram (AI-ECG) in adults. Here, we aim...

Lead Reconstruction Using Artificial Neural Networks for Ambulatory ECG Acquisition.

Sensors (Basel, Switzerland)
One of the most powerful techniques to diagnose cardiovascular diseases is to analyze the electrocardiogram (ECG). To increase diagnostic sensitivity, the ECG might need to be acquired using an ambulatory system, as symptoms may occur during a patien...

Overview of featurization techniques used in traditional versus emerging deep learning-based algorithms for automated interpretation of the 12-lead ECG.

Journal of electrocardiology
Automated interpretation of the 12-lead ECG has remained an underpinning interest in decades of research that has seen a diversity of computing applications in cardiology. The application of computers in cardiology began in the 1960s with early resea...

Ensemble of Deep Learning Models for Sleep Apnea Detection: An Experimental Study.

Sensors (Basel, Switzerland)
Sleep Apnea is a breathing disorder occurring during sleep. Older people suffer most from this disease. In-time diagnosis of apnea is needed which can be observed by the application of a proper health monitoring system. In this work, we focus on Obst...

Deep learning methods for screening patients' S-ICD implantation eligibility.

Artificial intelligence in medicine
Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T Wave Over Sensing (TWOS) is an inherent risk with S-ICDs which can lead to inappropriate shocks. A m...

The Role of Deep Learning-Based Echocardiography in the Diagnosis and Evaluation of the Effects of Routine Anti-Heart-Failure Western Medicines in Elderly Patients with Acute Left Heart Failure.

Journal of healthcare engineering
OBJECTIVE: The role of deep learning-based echocardiography in the diagnosis and evaluation of the effects of routine anti-heart-failure Western medicines was investigated in elderly patients with acute left heart failure (ALHF).

Machine Learning for personalised stress detection: Inter-individual variability of EEG-ECG markers for acute-stress response.

Computer methods and programs in biomedicine
Stress appears as a response for a broad variety of physiological stimuli. It does vary among individuals in amplitude, phase and frequency. Thus, the necessity for personalised diagnosis is key to prevent stress-related diseases. In order to evaluat...

A Sensing System Based on Public Cloud to Monitor Indoor Environment of Historic Buildings.

Sensors (Basel, Switzerland)
Monitoring the indoor environment of historic buildings helps to identify potential risks, provide guidelines for improving regular maintenance, and preserve cultural artifacts. However, most of the existing monitoring systems proposed for historic b...

A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia.

Sensors (Basel, Switzerland)
Atrial fibrillation (AF) is the most common cardiovascular disease (CVD), and most existing algorithms are usually designed for the diagnosis (i.e., feature classification) or prediction of AF. Artificial intelligence (AI) algorithms integrate the di...