Heart disease is one of the leading causes of mortality throughout the world. Among the
different heart diagnosis techniques, an electrocardiogram (ECG) is the least expensive non …

The growing number of applications of machine learning and data mining in many domains—
from agriculture to business, education, industrial manufacturing, and medicine—gave rise …

The field of eXplainable Artificial Intelligence (XAI) has witnessed significant advancements
in recent years. However, the majority of progress has been concentrated in the domains of …

Next-generation mobile networks will increasingly rely on the ability to forecast traffic
patterns for resource management. Usually, this translates into forecasting diverse …

COVID-19 is a positive-sense single-stranded RNA virus caused by a strain of coronavirus,
severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several noteworthy …

With the continuous increase of deep learning applications in safety critical systems, the
need for an interpretable decision-making process has become a priority within the research …

Variance estimation has been one of the key challenges in time series analysis for a long
time. Although many ARCHtype algorithms are widely applied in variance estimation, they …

We propose a new pruning constraint when mining frequent temporal patterns to be used as
classification and prediction features, the Semantic Adjacency Criterion [SAC], which filters …

Classifying body movement time series has supported decision-making in many medical
specialties, such as Neurology and Psychiatry. However, a protocol-guided review of the …

First, a procedure is developed for providing a multicriteria model-agnostic Counterfactual
Explanation (CE) for classifiers, which is formalized as a constrained multi-objective …