Arrhythmias

Applying Artificial Intelligence to ECG Analysis: Promise of a Better Future.

Integrated artificial neural network analysis and functional cell based affinity mass spectrometry for screening a bifunctional activator of Ca and βAR in aconite.

Arrhythmia, a common heart disease, is an abnormal frequency or rhythm of heartbeat caused by the or...

Robot-assisted ultrasound navigation platform for 3D HIFU treatment planning: Initial evaluation for conformal interstitial ablation.

Interstitial Ultrasound-guided High Intensity Focused Ultrasound (USgHIFU) therapy has the potential...

ECG Biometrics Using Deep Learning and Relative Score Threshold Classification.

The field of biometrics is a pattern recognition problem, where the individual traits are coded, reg...

Toward Task Autonomy in Robotic Cardiac Ablation: Learning-Based Kinematic Control of Soft Tendon-Driven Catheters.

The goal of this study was to propose and validate a control framework with level-2 autonomy (task a...

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology.

Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense ex...

Using the VQ-VAE to improve the recognition of abnormalities in short-duration 12-lead electrocardiogram records.

BACKGROUND AND OBJECTIVE: Morphological diagnosis is a basic clinical task of the short-duration 12-...

An Efficient and Robust Deep Learning Method with 1-D Octave Convolution to Extract Fetal Electrocardiogram.

The invasive method of fetal electrocardiogram (fECG) monitoring is widely used with electrodes dire...

Continuous blood pressure measurement from one-channel electrocardiogram signal using deep-learning techniques.

Continuous blood pressure (BP) measurement is crucial for reliable and timely hypertension detection...

Machine learning-based risk prediction of intrahospital clinical outcomes in patients undergoing TAVI.

BACKGROUND: Currently, patient selection in TAVI is based upon a multidisciplinary heart team assess...

Assessing the perforation site of cardiac tamponade during radiofrequency catheter ablation using gas analysis of pericardial effusion.

BACKGROUND: The incidence of pericardial effusion (PE) during radiofrequency catheter ablation (CA) ...

Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices.

Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagno...

Missing Value Estimation Methods Research for Arrhythmia Classification Using the Modified Kernel Difference-Weighted KNN Algorithms.

Electrocardiogram (ECG) signal is critical to the classification of cardiac arrhythmia using some ma...

Artificial Intelligence-Enabled ECG: a Modern Lens on an Old Technology.

PURPOSE OF REVIEW: To (i) review the concept of artificial intelligence (AI); (ii) summarize recent ...

How Will Machine Learning Inform the Clinical Care of Atrial Fibrillation?

Machine learning applications in cardiology have rapidly evolved in the past decade. With the availa...

Machine Learning of 12-Lead QRS Waveforms to Identify Cardiac Resynchronization Therapy Patients With Differential Outcomes.

BACKGROUND: Cardiac resynchronization therapy (CRT) improves heart failure outcomes but has signific...

Comparing the Bone Healing After Cold Ablation Robot-Guided Er:YAG Laser Osteotomy and Piezoelectric Osteotomy-A Pilot Study in a Minipig Mandible.

BACKGROUND AND OBJECTIVE: To take major advantage of erbium-doped yttrium aluminium garnet (Er:YAG) ...

In-Hospital Prognostic Value of Electrocardiographic Parameters Other Than ST-Segment Changes in Acute Myocardial Infarction: Literature Review and Future Perspectives.

Electrocardiography (ECG) remains an irreplaceable tool in the management of the patients with myoca...

Localization of origins of premature ventricular contraction in the whole ventricle based on machine learning and automatic beat recognition from 12-lead ECG.

OBJECTIVE: The localization of origins of premature ventricular contraction (PVC) is the key factor ...

Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review.

BACKGROUND: The electrocardiogram (ECG) is one of the most commonly used diagnostic tools in medicin...

Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study.

BACKGROUND: Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple heart abnorm...