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Personalized anomaly detection in PPG data using representation learning and biometric identification
Data-efficient machine learning methods in the ME-TIME study: Rationale and design of a longitudinal study to detect atrial fibrillation and heart failure from wearables
Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability
Benchmarking Outlier Detection Methods for Detecting IEM Patients in Untargeted Metabolomics Data
Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course
Machine Learning for Cardiovascular Outcomes from Wearable Data: Systematic Review from a Technology Readiness Level Point of View
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