This survey presents a comprehensive review of current literature on Explainable Artificial
Intelligence (XAI) methods for cyber security applications. Due to the rapid development of …

Potential benefits of precision medicine in cardiovascular disease (CVD) include more
accurate phenoty** of individual patients with the same condition or presentation, using …

By integrating sensing, memory and processing functionalities, biological nervous systems
are energy and area efficient. Emulating such capabilities in artificial systems is, however …

Temporal data, notably time series and spatio-temporal data, are prevalent in real-world
applications. They capture dynamic system measurements and are produced in vast …

Multimodal biomedical data fusion plays a pivotal role in distilling comprehensible and
actionable insights by seamlessly integrating disparate biomedical data from multiple …

Objective: Vast 12-lead ECGs repositories provide opportunities to develop new machine
learning approaches for creating accurate and automatic diagnostic systems for cardiac …

Recently, much effort has been put into solving arrhythmia classification problems with
machine learning-based methods. However, inter-heartbeat dependencies have been …

Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …

Electrocardiogram (ECG) recordings are indicative for the state of the human heart.
Automatic analysis of these recordings can be performed using various computational …

Electrocardiography (ECG) is a very common, non-invasive diagnostic procedure and its
interpretation is increasingly supported by algorithms. The progress in the field of automatic …