Atrial Fibrillation Detection

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

16 shown of 16 papers with code (43 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification
  9 Dec 2020 2 repositories listed
  Considering the quasi-periodic characteristics of ECG signals, the dynamic features can be extracted from the TMF images with the transfer learning pre-trained convolutional neural network (CNN) models.
• BayesBeat: Reliable Atrial Fibrillation Detection from Noisy Photoplethysmography Data
  2 Nov 2020 2 repositories listed
  Smartwatches or fitness trackers have garnered a lot of popularity as potential health tracking devices due to their affordable and longitudinal monitoring capabilities.
• Efficient Multi-View Fusion and Flexible Adaptation to View Missing in Cardiovascular System Signals
  13 Jun 2024 1 repository listed
  The progression of deep learning and the widespread adoption of sensors have facilitated automatic multi-view fusion (MVF) about the cardiovascular system (CVS) signals.
• SQUWA: Signal Quality Aware DNN Architecture for Enhanced Accuracy in Atrial Fibrillation Detection from Noisy PPG Signals
  15 Apr 2024 1 repository listed
  Atrial fibrillation (AF), a common cardiac arrhythmia, significantly increases the risk of stroke, heart disease, and mortality.
• SiamAF: Learning Shared Information from ECG and PPG Signals for Robust Atrial Fibrillation Detection
  13 Oct 2023 1 repository listed
  Previous deep learning models learn from a single modality, either electrocardiogram (ECG) or photoplethysmography (PPG) signals.
• Contrastive Self-Supervised Learning Based Approach for Patient Similarity: A Case Study on Atrial Fibrillation Detection from PPG Signal
  22 Jul 2023 1 repository listed
  In this paper, we propose a novel contrastive learning based deep learning framework for patient similarity search using physiological signals.
• Sparse learned kernels for interpretable and efficient medical time series processing
  6 Jul 2023 1 repository listed
  Rapid, reliable, and accurate interpretation of medical time-series signals is crucial for high-stakes clinical decision-making.
• Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia Alarms
  7 Nov 2022 1 repository listed
  To address this challenge, in this study, we propose to leverage AF alarms from bedside patient monitors to label concurrent PPG signals, resulting in the largest PPG-AF dataset so far (8.
• Efficient ECG-based Atrial Fibrillation Detection via Parameterised Hypercomplex Neural Networks
  27 Oct 2022 1 repository listed
  Atrial fibrillation (AF) is the most common cardiac arrhythmia and associated with a high risk for serious conditions like stroke.
• Exploring novel algorithms for atrial fibrillation detection by driving graduate level education in medical machine learning
  7 Jul 2022 1 repository listed
  During the lockdown of universities and the COVID-Pandemic most students were restricted to their homes.
• Investigating Deep Learning Benchmarks for Electrocardiography Signal Processing
  9 Apr 2022 1 repository listed
  In recent years, deep learning has witnessed its blossom in the field of Electrocardiography (ECG) processing, outperforming traditional signal processing methods in various tasks, for example, classification, QRS…
• End-to-End Optimized Arrhythmia Detection Pipeline using Machine Learning for Ultra-Edge Devices
  23 Nov 2021 1 repository listed
  The feature engineering employed in this research catered to optimizing the resource-efficient classifier used in the proposed pipeline, which was able to outperform the best performing standard ML model by 10⁵× in…
• Atrial Fibrillation Detection and ECG Classification based on CNN-BiLSTM
  12 Nov 2020 1 repository listed
  It is challenging to visually detect heart disease from the electrocardiographic (ECG) signals.
• Construe: a software solution for the explanation-based interpretation of time series
  17 Mar 2020 1 repository listed
  This paper presents a software implementation of a general framework for time series interpretation based on abductive reasoning.
• End-to-end Deep Learning from Raw Sensor Data: Atrial Fibrillation Detection using Wearables
  27 Jul 2018 1 repository listed
  We present a convolutional-recurrent neural network architecture with long short-term memory for real-time processing and classification of digital sensor data.
• Detection of Paroxysmal Atrial Fibrillation using Attention-based Bidirectional Recurrent Neural Networks
  7 May 2018 1 repository listed
  We also demonstrate the cross-domain generalizablity of the approach by adapting the learned model parameters from one recording modality (ECG) to another (photoplethysmogram) with improved AF detection performance.