A comprehensive survey on heart sound analysis in the deep learning era
Heart sound auscultation has been applied in clinical usage for early screening of
cardiovascular diseases. Due to the high demand for auscultation expertise, automatic …
cardiovascular diseases. Due to the high demand for auscultation expertise, automatic …
Systematic literature review with bibliometric analysis on Markov switching model: Methods and applications
This study involved a systematic literature review using bibliometric analysis to examine the
evolution and current trends of Markov switching studies. The bibliometric analysis was used …
evolution and current trends of Markov switching studies. The bibliometric analysis was used …
Dynamic regime differences in the market behavior of primary natural resources in response to geopolitical risk and economic policy uncertainty
The study explores the dynamic effects of geopolitical risks and economic policy
uncertainties on oil and natural gas prices in the US market's less volatile and highly volatile …
uncertainties on oil and natural gas prices in the US market's less volatile and highly volatile …
Diagnosis of heart diseases by a secure internet of health things system based on autoencoder deep neural network
Objective of this study is to introduce a secure IoHT system, which acts as a clinical decision
support system with the diagnosis of cardiovascular diseases. In this sense, it was …
support system with the diagnosis of cardiovascular diseases. In this sense, it was …
A robust interpretable deep learning classifier for heart anomaly detection without segmentation
Traditionally, abnormal heart sound classification is framed as a three-stage process. The
first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; …
first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; …
Short-segment heart sound classification using an ensemble of deep convolutional neural networks
This paper proposes a framework based on deep convolutional neural networks (CNNs) for
automatic heart sound classification using short-segments of individual heart beats. We …
automatic heart sound classification using short-segments of individual heart beats. We …
PCG classification through spectrogram using transfer learning
Heart rate classification is a challenging problem primarily due to spectral overlap of normal
heart sound with internal sources like extra heart sounds, extra systole, murmurs, respiration …
heart sound with internal sources like extra heart sounds, extra systole, murmurs, respiration …
Heart sounds classification based on feature fusion using lightweight neural networks
S Li, F Li, S Tang, F Luo - IEEE Transactions on instrumentation …, 2021 - ieeexplore.ieee.org
Heart sounds are an important basis for evaluating heart disease. In recent years, auxiliary
diagnosis technology of cardiovascular disease based on the detection of heart sound …
diagnosis technology of cardiovascular disease based on the detection of heart sound …
Research of heart sound classification using two-dimensional features
M Xiang, J Zang, J Wang, H Wang, C Zhou, R Bi… - … Signal Processing and …, 2023 - Elsevier
Background Heart sound plays a vital role to achieve an accurate diagnosis of
cardiovascular diseases, and its auxiliary diagnosis methods have become a hotspot. Aim …
cardiovascular diseases, and its auxiliary diagnosis methods have become a hotspot. Aim …
A new approach for the detection of abnormal heart sound signals using TQWT, VMD and neural networks
Phonocardiogram (PCG) plays an important role in evaluating many cardiac abnormalities,
such as the valvular heart disease, congestive heart failure and anatomical defects of the …
such as the valvular heart disease, congestive heart failure and anatomical defects of the …