ReviewArrhythmia & electrophysiology review2023
Artificial Intelligence for the Detection and Treatment of Atrial Fibrillation.
Review in Arrhythmia & electrophysiology review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.
- Machine learning in the prediction and detection of new-onset atrial fibrillation in ICU: a systematic review.Journal of anesthesia · 2024Pooled it
- Systematic, randomized atrial fibrillation screening using detailed phenotyping with a risk prediction model combined with patch electrocardiogram in a Swedish population aged 65 years or older: the CONSIDERING-AF trial.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Trial
- AI-Driven Atrial Fibrillation Management: From Signal to Strategy.Balkan medical journal · 2026Review
- Understanding the Diseased Atria.Physiology (Bethesda, Md.) · 2026Review
- AI-Based Phenotyping of Atrial Fibrillation Through Generative Topographic Mapping: Prospective Murcia Atrial Fibrillation Project III Cohort Study.Journal of medical Internet research · 2026Observational
- Applications of Left Atrial Strain in Cardiovascular Disease: A Comprehensive Review of Recent Evidence.Reviews in cardiovascular medicine · 2026Review
- Integrating AI-Driven Diagnostics in Arrhythmia Care to Enhance Patient Outcomes: A Narrative Review.Cureus · 2026Review
- Artificial Intelligence for Prediction and Detection of Atrial Fibrillation from Sinus-Rhythm Electrocardiograms and Ambulatory Monitoring.Biomedicines · 2026Review
- Artificial Intelligence-Electrocardiography to Predict Incident Atrial Fibrillation and Clinical Outcomes in Kidney Transplant Recipients.Kidney360 · 2026Article
- Empowering atrial fibrillation detection with TabPFN and SHAP interpretation based on ECG-derived features: a dual-center temporal validation study.BMC cardiovascular disorders · 2026Article
- A Deep Neural Network for Interpreting Wearable Electrocardiogram Data in Atrial Fibrillation: Prospective Observational Diagnostic Accuracy Study.JMIR mHealth and uHealth · 2026Observational
- Causal AI in Cardiac Arrhythmia: From Pattern Recognition to Mechanistic Insight.Clinical cardiology · 2026Review
- Large Language Modeling-Enabled Analysis of Atrial Fibrillation on Social Media.Journal of the American Heart Association · 2026Article
- Artificial Intelligence-driven Detection, Mapping, and Personalized Therapy for Atrial Fibrillation.The Journal of innovations in cardiac rhythm management · 2026Review
- Device-detected Atrial Fibrillation: How Much is Too Much?Arrhythmia & electrophysiology review · 2026Review
- Toward a National Health Digital and Data Architecture: Laying the Foundation for Digital Transformation: Commission on Investment Imperatives for a Healthy Nation.NAM perspectives · 2026Review
- Spatial Autocorrelation Dimension (Arrhythmia & electrophysiology review · 2026Review
- Atrial fibrillation in continuous flow-left ventricular assist device (CF-LVAD) patients: impact on pathophysiology.Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs · 2025Review
- Detection of atrial fibrillation via artificial intelligence-assisted auscultation.BMC cardiovascular disorders · 2025Article
- AI-ECG for early detection of atrial fibrillation: First-year results from a stroke prevention study in Shimizu, Japan.Journal of arrhythmia · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AF is the most common clinically relevant cardiac arrhythmia associated with multiple comorbidities, cardiovascular complications (e.g. stroke) and increased mortality. As artificial intelligence (AI) continues to transform the practice of medicine, this review article highlights specific applications of AI for the screening, diagnosis and treatment of AF. Routinely used digital devices and diagnostic technology have been significantly enhanced by these AI algorithms, increasing the potential for large-scale population-based screening and improved diagnostic assessments. These technologies have similarly impacted the treatment pathway of AF, identifying patients who may benefit from specific therapeutic interventions. While the application of AI to the diagnostic and therapeutic pathway of AF has been tremendously successful, the pitfalls and limitations of these algorithms must be thoroughly considered. Overall, the multifaceted applications of AI for AF are a hallmark of this emerging era of medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.