Results 11 to 20 of about 44,098 (253)

Machine Learning for Automated Classification of Abnormal Lung Sounds Obtained from Public Databases: A Systematic Review [PDF]

Bioengineering, 2023
Amos Lal, Vitaly Herasevich, Danielle Gerberi   +2 more
exaly   +2 more sources

Efficiently Classifying Lung Sounds through Depthwise Separable CNN Models with Fused STFT and MFCC Features [PDF]

Diagnostics, 2021
Shyan-Ming Yuan, Chuen-Tsai Sun, Chiahung Liao   +2 more
exaly   +2 more sources

Usefulness of Simulation Based Learning in First Year Medical Students: A Quasi-experimental Study [PDF]

Journal of Clinical and Diagnostic Research, 2022
Introduction: Auscultation of chest is an important part of clinical patient assessment and the skills required to interpret it are traditionally learned by listening the heart and lung sounds of many different patients.
Vinod Shende, Sachin Pawar, Suvarna Sande   +2 more
doaj   +1 more source

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Sensors, 2023
Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid ...
Arshia K. Sethi, Pratyusha Muddaloor, Priyanka Anvekar, Joshika Agarwal, Anmol Mohan, Mansunderbir Singh, Keerthy Gopalakrishnan, Ashima Yadav, Aakriti Adhikari, Devanshi Damani, Kanchan Kulkarni, Christopher A. Aakre, Alexander J. Ryu, Vivek N. Iyer, Shivaram P. Arunachalam   +14 more
doaj   +1 more source

Lung sound classification using wavelet transform and entropy to detect lung abnormality [PDF]

Serbian Journal of Electrical Engineering, 2022
Lung sounds provide essential information about the health of the lungs and respiratory tract. They have unique and distinguishable patterns associated with the abnormalities in these organs.
Rizal Achmad, Puspitasari Attika
doaj   +1 more source

Interpretation of Heart and Lungs Sounds Acquired via Remote, Digital Auscultation Reached Fair-to-Substantial Levels of Consensus among Specialist Physicians

Diagnostics, 2023
Background. Technological advancement may bridge gaps between long-practiced medical competencies and modern technologies. Such a domain is the application of digital stethoscopes used for physical examination in telemedicine.
Diana Magor, Evgeny Berkov, Dmitry Siomin, Eli Karniel, Nir Lasman, Liat Radinsky Waldman, Irina Gringauz, Shai Stern, Reut Lerner Kassif, Galia Barkai, Hadas Lewy, Gad Segal   +11 more
doaj   +1 more source

Detection of Respiratory Phases in a Breath Sound and Their Subsequent Utilization in a Diagnosis

Applied Sciences, 2021
Detection of lung sounds and their propagation is a powerful tool for analysing the behaviour of the respiratory system. A common approach to detect the respiratory sounds is lung auscultation, however, this method has significant limitations including ...
David Skalicky, Vaclav Koucky, Daniel Hadraba, Martin Viteznik, Martin Dub, Frantisek Lopot   +5 more
doaj   +1 more source

Data augmentation using Variational Autoencoders for improvement of respiratory disease classification.

PLoS ONE, 2022
Computerized auscultation of lung sounds is gaining importance today with the availability of lung sounds and its potential in overcoming the limitations of traditional diagnosis methods for respiratory diseases.
Jane Saldanha, Shaunak Chakraborty, Shruti Patil, Ketan Kotecha, Satish Kumar, Anand Nayyar   +5 more
doaj   +1 more source

Deep learning-based lung sound analysis for intelligent stethoscope

Military Medical Research, 2023
Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional stethoscopes have inherent limitations, such as inter-listener variability and subjectivity, and they cannot record respiratory sounds for offline ...
Dong-Min Huang, Jia Huang, Kun Qiao, Nan-Shan Zhong, Hong-Zhou Lu, Wen-Jin Wang   +5 more
doaj   +1 more source

Bayesian evaluation of the accuracy of a thoracic auscultation scoring system in dairy calves with bronchopneumonia using a standard lung sound nomenclature

Journal of Veterinary Internal Medicine, 2023
Background Although thoracic auscultation (AUSC) in calves is quick and easy to perform, the definition of lung sounds is highly variable and leads to poor to moderate accuracy in diagnosing bronchopneumonia (BP).
Antonio Boccardo, Salvatore Ferraro, Giulia Sala, Vincenzo Ferrulli, Davide Pravettoni, Sébastien Buczinski   +5 more
doaj   +1 more source