Recent advancements and applications of deep learning in heart failure: Α systematic review

G Petmezas, VE Papageorgiou, V Vassilikos… - Computers in Biology …, 2024 - Elsevier
Background Heart failure (HF), a global health challenge, requires innovative diagnostic and
management approaches. The rapid evolution of deep learning (DL) in healthcare …

Grand challenge on respiratory sound classification for sprsound dataset

Q Zhang, J Zhang, J Yuan, H Huang… - … Circuits and Systems …, 2023 - ieeexplore.ieee.org
Globally, respiratory diseases are the leading cause of death, making it essential to develop
an automatic respiratory sounds software to speed up diagnosis and reduce physician …

[HTML][HTML] GAN-SkipNet: A Solution for Data Imbalance in Cardiac Arrhythmia Detection Using Electrocardiogram Signals from a Benchmark Dataset

HM Rai, J Yoo, S Dashkevych - Mathematics, 2024 - mdpi.com
Electrocardiography (ECG) plays a pivotal role in monitoring cardiac health, yet the manual
analysis of ECG signals is challenging due to the complex task of identifying and …

Supervised Contrastive Learning Framework and Hardware Implementation of Learned ResNet for Real-time Respiratory Sound Classification

J Hu, CS Leow, S Tao, WL Goh… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
This paper presents a supervised contrastive learning (SCL) framework for respiratory
sound classification and the hardware implementation of learned ResNet on field …

[HTML][HTML] MDAR: A Multiscale Features-Based Network for Remotely Measuring Human Heart Rate Utilizing Dual-Branch Architecture and Alternating Frame Shifts in …

L Zhang, J Ren, S Zhao, P Wu - Sensors (Basel, Switzerland), 2024 - pmc.ncbi.nlm.nih.gov
Remote photoplethysmography (rPPG) refers to a non-contact technique that measures
heart rate through analyzing the subtle signal changes of facial blood flow captured by video …