Machine learning in arrhythmia and electrophysiology
Machine learning (ML), a branch of artificial intelligence, where machines learn from big
data, is at the crest of a technological wave of change swee** society. Cardiovascular …
data, is at the crest of a technological wave of change swee** society. Cardiovascular …
A deep learning algorithm to translate and classify cardiac electrophysiology
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 …
been a critical in vitro advance in the study of patient-specific physiology, pathophysiology …
Role of Machine Learning and Artificial Intelligence in Arrhythmias and Electrophysiology
MUR Gondal, HA Mehdi, RR Khenhrani… - Cardiology in …, 2024 - journals.lww.com
Abstract Machine learning (ML), a subset of artificial intelligence (AI) centered on machines
learning from extensive datasets, stands at the forefront of a technological revolution …
learning from extensive datasets, stands at the forefront of a technological revolution …
[HTML][HTML] Atrial fibrillation signatures on intracardiac electrograms identified by deep learning
Background Automatic detection of atrial fibrillation (AF) by cardiac devices is increasingly
common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events' …
common yet suboptimally groups AF, flutter or tachycardia (AT) together as 'high rate events' …
Learning for prevention of sudden cardiac death
NA Trayanova - Circulation research, 2021 - Am Heart Assoc
Sudden cardiac death (SCD) is a devastating event and a significant health care burden.
While coronary artery disease and overall cardiovascular deaths have declined significantly …
While coronary artery disease and overall cardiovascular deaths have declined significantly …
A deep learning algorithm to translate and classify cardiac electrophysiology: from iPSC-CMs to adult cardiac cells
Exciting developments in both in vitro and in silico technologies have led to new ways to
identify patient specific cardiac mechanisms. The development of induced pluripotent stem …
identify patient specific cardiac mechanisms. The development of induced pluripotent stem …
Intra-cardiac signatures of atrial arrhythmias identified by machine learning and traditional features
Intracardiac devices separate atrial arrhythmias (AA) from sinus rhythm (SR) using
electrogram (EGM) features such as rate, that are imperfect. We hypothesized that machine …
electrogram (EGM) features such as rate, that are imperfect. We hypothesized that machine …
A deep learning algorithm to translate and classify cardiac electrophysiology.
D Kernik, K Sakamoto, Y Kanda, J Kurokawa… - 2021 - escholarship.org
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 …
been a critical in vitro advance in the study of patient-specific physiology, pathophysiology …
[HTML][HTML] Echocardiographic Predictors of Arrhythmias in Phospholamban Mutation Carriers: A Glimpse Into the Future?
JL Jefferies - Cardiovascular Imaging, 2021 - jacc.org
—Charles Dickens (1) In this issue of iJACC, Taha et al.(2) report their longitudinal cohort
data on the use of early echocardiographic findings to establish risk profiles in adults with …
data on the use of early echocardiographic findings to establish risk profiles in adults with …