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What is Atrial Fibrillation Detection From Ambulatory ECG With Accelerometry about?
This paper presents a semi-supervised learning (SSL) approach for detecting atrial fibrillation (AF) from ambulatory ECG data, utilizing a variational autoencoder (VAE) that incorporates accelerometry data to enhance model performance. The model was trained on a large dataset of over 72,000 patients and demonstrated over 91% accuracy with only 20% of the training data being labeled. The study highlights the effectiveness of SSL in improving AF detection while addressing the challenges of limited labeled dat
- Author
- dudu bubu
- Language
- EN