Medical time series are sequential data collected over time that measures health-related
signals, such as electroencephalography (EEG), electrocardiography (ECG), and intensive …

The origin of the COVID-19 pandemic has given overture to redirection, as well as
innovation to many digital technologies. Even after the progression of vaccination efforts …

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 …

Symbolic learning is the logic-based approach to machine learning, and its mission is to
provide algorithms and methodologies to extract logical information from data and express it …

We present an experimental investigation into the effectiveness of transfer learning and
bottleneck feature extraction in detecting COVID-19 from audio recordings of cough, breath …

This paper presents the Coswara dataset, a dataset containing diverse set of respiratory
sounds and rich meta-data, recorded between April-2020 and February-2022 from 2635 …

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 …

Quantum-inspired Machine Learning (QiML) is a burgeoning field, receiving global attention
from researchers for its potential to leverage principles of quantum mechanics within …

Artificial intelligence (AI) capabilities have grown rapidly with the introduction of cutting-edge
deep-model architectures and learning strategies. Explainable AI (XAI) methods aim to …

Alongside the currently used nasal swab testing, the COVID-19 pandemic situation would
gain noticeable advantages from low-cost tests that are available at any-time, anywhere, at a …