22 citations · 34 across the 23 of their papers we have counts for
5 papers · 1 filter
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Imbalanced data distributions are prevalent in real-world scenarios, posing significant challenges in both imbalanced classification and imbalanced regression tasks. They often cau…
Deep Imbalanced Regression to Estimate Vascular Age from PPG Data: a Novel Digital Biomarker for Cardiovascular Health
Guangkun Nie, Qinghao Zhao, Gongzheng Tang +2
Photoplethysmography (PPG) is emerging as a crucial tool for monitoring human hemodynamics, with recent studies highlighting its potential in assessing vascular aging through deep…
Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series
Shuhao Mei, Xin Li, Yuxi Zhou +9
Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent fe…
A Deep Learning Method for Beat-Level Risk Analysis and Interpretation of Atrial Fibrillation Patients during Sinus Rhythm
Jun Lei, Yuxi Zhou, Xue Tian +5
Atrial Fibrillation (AF) is a common cardiac arrhythmia. Many AF patients experience complications such as stroke and other cardiovascular issues. Early detection of AF is crucial.…
A Scoping Review of Deep Learning Methods for Photoplethysmography Data
Guangkun Nie, Jiabao Zhu, Gongzheng Tang +4
Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad deployment in both clinical monitoring…