[HTML][HTML] 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 …
[HTML][HTML] 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 …
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 …
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 contrastive embedding-based domain adaptation method for lung sound recognition in children community-acquired pneumonia
Lung sound analysis has been used for assessing the lung conditions of children with
community-acquired pneumonia (CAP). However, the inconsistent data distribution, caused …
community-acquired pneumonia (CAP). However, the inconsistent data distribution, caused …
An effective lung sound classification system for respiratory disease diagnosis using densenet cnn model with sound pre-processing engine
WB Ma, XY Deng, Y Yang… - 2022 IEEE Biomedical …, 2022 - ieeexplore.ieee.org
Lung sound auscultation is a simple, inexpensive, and non-invasive method of diagnosing
respiratory diseases. But the experience of each physician may be different, resulting in …
respiratory diseases. But the experience of each physician may be different, resulting in …
Training one model to detect heart and lung sound events from single point auscultations
L Melms, RR Ilesan, U Köhler, O Hildebrandt… - arXiv preprint arXiv …, 2023 - arxiv.org
Objective: This work proposes a semi-supervised training approach for detecting lung and
heart sounds simultaneously with only one trained model and in invariance to the …
heart sounds simultaneously with only one trained model and in invariance to the …
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 …
Audio-based deep learning frameworks for detecting covid-19
This paper evaluates a wide range of audio-based deep learning frameworks applied to the
breathing, cough, and speech sounds for detecting COVID-19. In general, the audio …
breathing, cough, and speech sounds for detecting COVID-19. In general, the audio …
Rene: A Pre-trained Multi-modal Architecture for Auscultation of Respiratory Diseases
P Zhang, Z Zheng, S Zhang, M Yang, S Tang - arXiv preprint arXiv …, 2024 - arxiv.org
This study presents a novel methodology utilizing a pre-trained speech recognition model
for processing respiratory sound data. By incorporating medical record information, we …
for processing respiratory sound data. By incorporating medical record information, we …