Deep learning-based lung sound analysis for intelligent stethoscope
Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …
stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and …
Benchmarking of eight recurrent neural network variants for breath phase and adventitious sound detection on a self-developed open-access lung sound database …
FS Hsu, SR Huang, CW Huang, CJ Huang… - PLoS …, 2021 - journals.plos.org
A reliable, remote, and continuous real-time respiratory sound monitor with automated
respiratory sound analysis ability is urgently required in many clinical scenarios—such as in …
respiratory sound analysis ability is urgently required in many clinical scenarios—such as in …
[HTML][HTML] Cochleogram-based adventitious sounds classification using convolutional neural networks
LD Mang, FJ Cañadas-Quesada… - … Signal Processing and …, 2023 - Elsevier
Abstract Background: The World Health Organization (WHO) establishes as a top priority the
early detection of respiratory diseases. This detection could be performed by means of …
early detection of respiratory diseases. This detection could be performed by means of …
Classify respiratory abnormality in lung sounds using stft and a fine-tuned resnet18 network
Recognizing patterns in lung sounds is crucial to detecting and monitoring respiratory
diseases. Current techniques for analyzing respiratory sounds demand domain experts and …
diseases. Current techniques for analyzing respiratory sounds demand domain experts and …
Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review
Pulmonary auscultation is essential for detecting abnormal lung sounds during physical
assessments, but its reliability depends on the operator. Machine learning (ML) models offer …
assessments, but its reliability depends on the operator. Machine learning (ML) models offer …
An ensemble of deep learning frameworks for predicting respiratory anomalies
This paper evaluates a range of deep learning frameworks for detecting respiratory
anomalies from input audio. Audio recordings of respiratory cycles collected from patients …
anomalies from input audio. Audio recordings of respiratory cycles collected from patients …
A novel melspectrogram snippet representation learning framework for severity detection of chronic obstructive pulmonary diseases
A chronic obstructive pulmonary disease (COPD) is a major public health concern across
the world. Since it is an incurable disease, early detection and accurate diagnosis are very …
the world. Since it is an incurable disease, early detection and accurate diagnosis are very …
A feature polymerized based two-level ensemble model for respiratory sound classification
L Zhang, Y Zhu, S Tu, L Xu - 2022 IEEE Biomedical Circuits and …, 2022 - ieeexplore.ieee.org
Accurate analysis and classification of respiratory sound play an important role in the
diagnosis of respiratory diseases. Most of the current methods for classifying respiratory …
diagnosis of respiratory diseases. Most of the current methods for classifying respiratory …
[PDF][PDF] HISET: Hybrid interpretable strategies with ensemble techniques for respiratory sound classification
SK Prabhakar, DO Won - Heliyon, 2023 - cell.com
The human respiratory systems can be affected by several diseases and it is associated with
distinctive sounds. For advanced biomedical signal processing, one of the most complex …
distinctive sounds. For advanced biomedical signal processing, one of the most complex …
An ensemble of deep learning frameworks applied for predicting respiratory anomalies
In this paper, we evaluate various deep learning frameworks for detecting respiratory
anomalies from input audio recordings. To this end, we firstly transform audio respiratory …
anomalies from input audio recordings. To this end, we firstly transform audio respiratory …