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 …

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 …

Forest fires are the main cause of desertification, and they have a disastrous impact on
agricultural and forest ecosystems. Modern fire detection and warning systems rely on …

Sound signals from the respiratory system are largely taken as tokens of human health.
Early diagnosis of respiratory tract diseases is of great importance because, if delayed, it …

Respiratory diseases represent a significant global burden, necessitating efficient diagnostic
methods for timely intervention. Digital biomarkers based on audio, acoustics, and sound …

Method In this research, Supervised Learning classification algorithms have been used,
which include Support Vector Machine (SVM), random forest, and Artificial Neural Networks …

Artificial Intelligence has seen a significant resurgence in the past decade in wide ranging
technology and domain areas. Recent progress in digitisation and high influx of biomedical …

Pneumonia is a serious disease often accompanied by complications, sometimes leading to
death. Unfortunately, diagnosis of pneumonia is frequently delayed until physical and …

Introduction The Coronavirus disease 2019 (COVID-19) pandemic has caused irreparable
damage to the world. In order to prevent the spread of pathogenicity, it is necessary to …

The objectives of this research are analysing the performance of the state-of-the-art machine
learning techniques for classifying COVID-19 from cough sound and identifying the model …