Federated learning for healthcare domain-pipeline, applications and challenges

M Joshi, A Pal, M Sankarasubbu - ACM Transactions on Computing for …, 2022 - dl.acm.org
Federated learning is the process of developing machine learning models over datasets
distributed across data centers such as hospitals, clinical research labs, and mobile devices …

Cough sound detection and diagnosis using artificial intelligence techniques: challenges and opportunities

KS Alqudaihi, N Aslam, IU Khan, AM Almuhaideb… - Ieee …, 2021 - ieeexplore.ieee.org
Coughing is a common symptom of several respiratory diseases. The sound and type of
cough are useful features to consider when diagnosing a disease. Respiratory infections …

Explainable AI for clinical and remote health applications: a survey on tabular and time series data

F Di Martino, F Delmastro - Artificial Intelligence Review, 2023 - Springer
Abstract Nowadays Artificial Intelligence (AI) has become a fundamental component of
healthcare applications, both clinical and remote, but the best performing AI systems are …

COVID-19 cough classification using machine learning and global smartphone recordings

M Pahar, M Klopper, R Warren, T Niesler - Computers in Biology and …, 2021 - Elsevier
We present a machine learning based COVID-19 cough classifier which can discriminate
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …

Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method

NK Chowdhury, MA Kabir, MM Rahman… - Computers in Biology …, 2022 - Elsevier
This research aims to analyze the performance of state-of-the-art machine learning
techniques for classifying COVID-19 from cough sounds and to identify the model (s) that …

Exploring automatic COVID-19 diagnosis via voice and symptoms from crowdsourced data

J Han, C Brown, J Chauhan… - ICASSP 2021-2021 …, 2021 - ieeexplore.ieee.org
The development of fast and accurate screening tools, which could facilitate testing and
prevent more costly clinical tests, is key to the current pandemic of COVID-19. In this context …

[HTML][HTML] Towards using cough for respiratory disease diagnosis by leveraging Artificial Intelligence: A survey

A Ijaz, M Nabeel, U Masood, T Mahmood… - Informatics in Medicine …, 2022 - Elsevier
Cough acoustics contain multitudes of vital information about pathomorphological
alterations in the respiratory system. Reliable and accurate detection of cough events by …

AI-Based human audio processing for COVID-19: A comprehensive overview

G Deshpande, A Batliner, BW Schuller - Pattern recognition, 2022 - Elsevier
Abstract The Coronavirus (COVID-19) pandemic impelled several research efforts, from
collecting COVID-19 patients' data to screening them for virus detection. Some COVID-19 …

Automated, multiparametric monitoring of respiratory biomarkers and vital signs in clinical and home settings for COVID-19 patients

X Ni, W Ouyang, H Jeong, JT Kim… - Proceedings of the …, 2021 - National Acad Sciences
Capabilities in continuous monitoring of key physiological parameters of disease have never
been more important than in the context of the global COVID-19 pandemic. Soft, skin …

CR19: A framework for preliminary detection of COVID-19 in cough audio signals using machine learning algorithms for automated medical diagnosis applications

EED Hemdan, W El-Shafai, A Sayed - Journal of Ambient Intelligence and …, 2023 - Springer
Today, there is a level of panic and chaos dominating the entire world due to the massive
outbreak in the second wave of COVID-19 disease. As the disease has numerous symptoms …