1 citations · 2 across the 4 of their papers we have counts for
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Reconsideration on evaluation of machine learning models in continuous monitoring using wearables
Cheng Ding, Zhicheng Guo, Cynthia Rudin +3
This paper explores the challenges in evaluating machine learning (ML) models for continuous health monitoring using wearable devices beyond conventional metrics. We state the comp…
Photoplethysmography based atrial fibrillation detection: an updated review from July 2019
Cheng Ding, Ran Xiao, Weijia Wang +2
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant health ramifications, including an elevated susceptibility to ischemic stroke, heart disease,…
SiamAF: Learning Shared Information from ECG and PPG Signals for Robust Atrial Fibrillation Detection
Zhicheng Guo, Cheng Ding, Duc H. Do +4
Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. It is associated with an increased risk of stroke, heart failure, and other cardiovascular complications, bu…
A Self-Supervised Algorithm for Denoising Photoplethysmography Signals for Heart Rate Estimation from Wearables
Pranay Jain, Cheng Ding, Cynthia Rudin +1
Smart watches and other wearable devices are equipped with photoplethysmography (PPG) sensors for monitoring heart rate and other aspects of cardiovascular health. However, PPG sig…
Sparse learned kernels for interpretable and efficient medical time series processing
Sully F. Chen, Zhicheng Guo, Cheng Ding +2
Rapid, reliable, and accurate interpretation of medical time-series signals is crucial for high-stakes clinical decision-making. Deep learning methods offered unprecedented perform…