The convergence of drones with the Internet of Things (IoT) has paved the way for the
Internet of Drones (IoD), an interconnected network of drones, ground control systems, and …

Millions of humans worldwide have been impacted by consecutive COVID-19 waves during
the past three years. The correct treatment for COVID-19 has not yet been identified because …

Background Epilepsy is a neurological illness affecting the brain that makes people more
likely to experience frequent, spontaneous seizures. There has to be an accurate automated …

Explainable artificial intelligence (XAI) can help build trust between AI models and
healthcare professionals in the context of medical image classification. XAI can help explain …

There is a growing trend of using artificial intelligence, particularly deep learning algorithms,
in medical diagnostics, revolutionizing healthcare by improving efficiency, accuracy, and …

Early detection of atrial fibrillation (AF) is crucial for its effective management and prevention.
Various methods for detecting AF using deep learning (DL) based on supervised learning …

An increasing demand for model explainability has accompanied the widespread adoption
of transformers in various fields of applications. In this paper, we conduct a survey of the …

The COVID-19 virus is increasingly crucial to human health since new variants appear
frequently. Detection of COVID-19 through respiratory sound has been an important area of …

In healthcare there is a pursuit for employing interpretable algorithms to assist healthcare
professionals in several decision scenarios. Following the Predictive, Descriptive and …

Explainability is an aspect of modern AI that is vital for impact and usability in the real world.
The main objective of this paper is to emphasise the need to understand the predictions of …