AIMC Topic: Electrophysiologic Techniques, Cardiac

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A deep learning algorithm to translate and classify cardiac electrophysiology.

eLife
The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network ...

Machine Learning in Arrhythmia and Electrophysiology.

Circulation research
Machine learning (ML), a branch of artificial intelligence, where machines learn from big data, is at the crest of a technological wave of change sweeping society. Cardiovascular medicine is at the forefront of many ML applications, and there is a si...

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology.

Circulation. Arrhythmia and electrophysiology
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of intense exploration, showing potential to automate human tasks and even perform tasks beyond human capabilities. Literacy and understanding of AI/ML methods are...

Strain Curve Classification Using Supervised Machine Learning Algorithm with Physiologic Constraints.

Ultrasound in medicine & biology
Speckle tracking echocardiography (STE) enables quantification of myocardial deformation by a generation of spatiotemporal strain curves or time-strain curves (TSCs). Currently, only assessment of peak global longitudinal strain is employed in clinic...

Rethinking multiscale cardiac electrophysiology with machine learning and predictive modelling.

Computers in biology and medicine
We review some of the latest approaches to analysing cardiac electrophysiology data using machine learning and predictive modelling. Cardiac arrhythmias, particularly atrial fibrillation, are a major global healthcare challenge. Treatment is often th...

Catheter Ablation of Focal Atrial Tachycardia Using Remote Magnetic Navigation.

The Journal of invasive cardiology
OBJECTIVES: The outcomes of catheter ablation in focal atrial tachycardia (AT) using remote magnetic navigation (RMN) are still controversial. The objectives of this study were to assess the acute and long-term outcomes of catheter ablation in focal ...

Semi-supervised clustering of fractionated electrograms for electroanatomical atrial mapping.

Biomedical engineering online
BACKGROUND: Electrogram-guided ablation procedures have been proposed as an alternative strategy consisting of either mapping and ablating focal sources or targeting complex fractionated electrograms in atrial fibrillation (AF). However, the incomple...