4 citations · 12 across the 4 of their papers we have counts for
4 papers
Transformer Meets Gated Residual Networks To Enhance Photoplethysmogram Artifact Detection Informed by Mutual Information Neural Estimation
Thanh-Dung Le, Clara Macabiau, Kévin Albert +3
This study delves into the effectiveness of various learning methods in improving Transformer models, focusing particularly on the Gated Residual Network Transformer (GRN-Transform…
A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection
Thanh-Dung Le, Clara Macabiau, Kévin Albert +2
Recent research at CHU Sainte Justine's Pediatric Critical Care Unit (PICU) has revealed that traditional machine learning methods, such as semi-supervised label propagation and K-…
Label Propagation Techniques for Artifact Detection in Imbalanced Classes using Photoplethysmogram Signals
Clara Macabiau, Thanh-Dung Le, Kevin Albert +3
This study aimed to investigate the application of label propagation techniques to propagate labels among photoplethysmogram (PPG) signals, particularly in imbalanced class scenari…
GRN-Transformer: Enhancing Motion Artifact Detection in PICU Photoplethysmogram Signals
Thanh-Dung Le, Clara Macabiau, Kévin Albert +2
Photoplethysmogram (PPG) signals, optical measurements of pulsatile blood flow used continuously in intensive care monitoring, are frequently contaminated by motion, low perfusion,…