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 …

Since December 2019, the global health population has faced the rapid spreading of
coronavirus disease (COVID-19). With the incremental acceleration of the number of …

In recent times, speech-based automatic disease detection systems have shown several
promising results in biomedical and life science applications, especially in the case of …

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 …

Audio deepfakes have been increasingly emerging as a potential source of deceit, with the
development of avant-garde methods of synthetic speech generation. Hence, differentiating …

COVID-19 infection segmentation has essential applications in determining the severity of a
COVID-19 patient and can provide a necessary basis for doctors to adopt a treatment …

For COVID-19, the need for robust, inexpensive, and accessible screening becomes critical.
Even though symptoms present differently, cough is still taken as one of the primary …

This study proposes a contrastive convolutional auto-encoder (contrastive CAE), a
combined architecture of an auto-encoder and contrastive loss, to identify individuals with …

Coronavirus has an impact on millions of lives and has been added to the important
pandemics that continue to affect with its variants. Since it is transmitted through the …

The Covid-19 pandemic is one of the most significant global health concerns that have
emerged in this decade. Intelligent healthcare technology and techniques based on speech …