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Reading Between the Leads: Local Lead-Attention Based Classification of Electrocardiogram Signals
Self-attention models have emerged as powerful tools in both computer vision and Natural Language Processing (NLP) domains.
Ranked #1 on
ECG Classification
on PhysioNet Challenge 2021
Learning Beyond Similarities: Incorporating Dissimilarities between Positive Pairs in Self-Supervised Time Series Learning
By identifying similarities between successive inputs, Self-Supervised Learning (SSL) methods for time series analysis have demonstrated their effectiveness in encoding the inherent static characteristics of temporal data.
Subject-based Non-contrastive Self-Supervised Learning for ECG Signal Processing
Supervised learning methods have successfully been used to identify specific aspects in the signal, like detection of rhythm disorders (arrhythmias).
DENS-ECG: A Deep Learning Approach for ECG Signal Delineation
Objectives: With the technological advancements in the field of tele-health monitoring, it is now possible to gather huge amounts of electro-physiological signals such as electrocardiogram (ECG).
