Federated learning for lung sound analysis
Despite the general success of employing artificial intelligence (AI) to help radiologists
perform computer-aided patient diagnosis, creating good models with tiny datasets at …
perform computer-aided patient diagnosis, creating good models with tiny datasets at …
Weighted aggregation through probability based ranking: An optimized federated learning architecture to classify respiratory diseases
AAS Shaikh, MS Bhargavi - Computer Methods and Programs in …, 2023 - Elsevier
Abstract Background and Objective Respiratory Diseases are one of the leading chronic
illnesses in the world according to the reports by World Health Organization. Diagnosing …
illnesses in the world according to the reports by World Health Organization. Diagnosing …
Transfer Learning Based Diagnosis and Analysis of Lung Sound Aberrations
H Gulzar, J Li, A Manzoor, S Rehmat, U Amjad… - arXiv preprint arXiv …, 2023 - arxiv.org
With the development of computer-systems that can collect and analyze enormous volumes
of data, the medical profession is establishing several non-invasive tools. This work attempts …
of data, the medical profession is establishing several non-invasive tools. This work attempts …
Different Transfer Learning Approaches for Recognition of Lung Sounds
JA Patel, M Patel - … on Artificial Intelligence and Smart Energy …, 2022 - ieeexplore.ieee.org
Lung disorders are currently the leading cause of mortality in the world. The majority of
instances of lung illness are discovered after the condition worsens to an advanced level; …
instances of lung illness are discovered after the condition worsens to an advanced level; …
Heart Sound Abnormality Detection From Multi-Institutional Collaboration: Introducing a Federated Learning Framework
Objective: Early diagnosis of cardiovascular diseases is a crucial task in medical practice.
With the application of computer audition in the healthcare field, artificial intelligence (AI) has …
With the application of computer audition in the healthcare field, artificial intelligence (AI) has …
Data augmentation using Variational Autoencoders for improvement of respiratory disease classification
J Saldanha, S Chakraborty, S Patil, K Kotecha… - Plos one, 2022 - journals.plos.org
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 …
of lung sounds and its potential in overcoming the limitations of traditional diagnosis …
Feature-based fusion using CNN for lung and heart sound classification
Lung or heart sound classification is challenging due to the complex nature of audio data, its
dynamic properties of time, and frequency domains. It is also very difficult to detect lung or …
dynamic properties of time, and frequency domains. It is also very difficult to detect lung or …
Improvise approach for respiratory pathologies classification with multilayer convolutional neural networks
Every respiratory-related checkup includes audio samples collected from the individual,
collected through different tools (sonograph, stethoscope). This audio is analyzed to identify …
collected through different tools (sonograph, stethoscope). This audio is analyzed to identify …
Accelerating Lung Disease Diagnosis: The Role of Federated Learning and CNN in Multi-Institutional Collaboration
This research employs federated learning using Convolutional Neural Networks (CNN)
across multi-institutional datasets to classify the severity of lung disease. The project …
across multi-institutional datasets to classify the severity of lung disease. The project …
Lung sound classification with multi-feature integration utilizing lightweight cnn model
Detecting respiratory diseases is of utmost importance, considering that respiratory ailments
represent one of the most prevalent categories of diseases globally. The initial stage of lung …
represent one of the most prevalent categories of diseases globally. The initial stage of lung …