A lightweight CNN model for detecting respiratory diseases from lung auscultation sounds using EMD-CWT-based hybrid scalogram
Listening to lung sounds through auscultation is vital in examining the respiratory system for
abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the …
abnormalities. Automated analysis of lung auscultation sounds can be beneficial to the …
Detecting respiratory diseases from recorded lung sounds by 2D CNN
Respiratory disease is among the leading causes of deaths around the world. A large
amount of population is being affected regularly with some kinds of lung function disorders …
amount of population is being affected regularly with some kinds of lung function disorders …
Neural networks for pulmonary disease diagnosis using auditory and demographic information
Pulmonary diseases impact millions of lives globally and annually. The recent outbreak of
the pandemic of the COVID-19, a novel pulmonary infection, has more than ever brought the …
the pandemic of the COVID-19, a novel pulmonary infection, has more than ever brought the …
Inception-Based Network and Multi-Spectrogram Ensemble Applied For Predicting Respiratory Anomalies and Lung Diseases
This paper presents an inception-based deep neural network for detecting lung diseases
using respiratory sound input. Recordings of respiratory sound collected from patients are …
using respiratory sound input. Recordings of respiratory sound collected from patients are …
Development of classification methods for wheeze and crackle using mel frequency cepstral coefficient (MFCC): A deep learning approach
TM Sadi, R Hassan - International Journal on Perceptive and …, 2020 - journals.iium.edu.my
The most common method used by physicians and pulmonologists to evaluate the state of
the lung is by listening to the acoustics of the patient's breathing by a stethoscope …
the lung is by listening to the acoustics of the patient's breathing by a stethoscope …