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Personalised Cardiac Modelling
Author(s): Ovais A Jaffery , Lea Melki , Gregory Slabaugh , et al Added: 1 year ago

Imaging & Diagnostics

Electrophysiology & Arrhythmia
EHRA 25: The CONSIDERING-AF Study
Author(s): Emma Sandgren Added: 10 months ago
EHRA 2025 - Outcomes from model screening for atrial fibrillation (AF) show the combination of a risk prediction model and long-term electrocardiogram (ECG) monitoring is superior to standard of care in detecting new cases of AF in a high-risk population aged 65 years or older. In the risk prediction model arm, the incidence of AF after six months was significantly higher than the incidence in… View more

Electrophysiology & Arrhythmia
AI-Enhanced ECG Model Accurately Predicts Future Complete Heart Block Risk
Added: 5 months ago Source:  Arrhythmia Academy
Complete heart block (CHB) is a life-threatening arrhythmia, yet current electrocardiography (ECG)-based methods for risk stratification have limited predictive power. A new study has detailed the development and validation of a novel artificial intelligence-enhanced ECG (AI-ECG) model that can accurately predict the risk of incident CHB, significantly outperforming traditional risk markers.¹The… View more

Digital Health

Electrophysiology & Arrhythmia
Research Area(s) / Expertise:
Research Area(s) / Expertise:
Causal Machine Learning for LAAO in Patients with AF
Author(s): Added: 11 months ago
How can a causal machine learning framework act as a decision-supporting tool to select patients for left atrial appendage occlusion (LAAO)?In this short interview, Dr Xiaoxi Yao (Mayo Clinic, Rochester, MN, US) discusses a study investigating the causal forest model learning framework to identify characteristics in atrial fibrillation patients which would benefit most from LAAO. Dr Yao explains… View more

Electrophysiology & Arrhythmia
Genetic Variants Improve AF Risk Prediction
Added: 3 months ago Source:  Arrhythmia Academy
Atrial fibrillation (AF) has a complex genetic architecture, and a new study suggests that integrating information on common, rare, and somatic genetic variants can significantly improve risk prediction. Researchers developed an integrated genomic model (IGM-AF) that, when combined with clinical factors, enhanced the stratification of individuals at risk for incident AF.¹This cohort study… View more

Demographic

Electrophysiology & Arrhythmia
Echocardiography-guided Percutaneous Transapical Septal Pacing
Author(s): Zhaohui Qiu , Xianhao Wu , Haiyan Chen , et al Added: 1 month ago

Electrophysiology & Arrhythmia

Imaging & Diagnostics
Amod Amritphale
Research Area(s) / Expertise:

Intervention

 Job title: Interventional Cardiologist and Director of Cardiovascular Research
DrAmod Amritphale is an interventional cardiologist and the Director of Cardiovascular Research at the University of South Alabama, AL, US. He is a pioneer and an authority in the use of artificial intelligence and machine learning models for predictive modelling and exploring core outcomes in cardiovascular disease.He is also extensively involved in research involving coronary artery disease,… View more
Real-world Outcomes of AVNA: 10-year Results
Author(s): Anette Caroline Kõre , Martin Serg , Tuljo Ööbik , et al Added: 5 days ago

Electrophysiology & Arrhythmia