This comprehensive review unfolds a detailed narrative of Artificial Intelligence (AI) making
its foray into radiology, a move that is catalysing transformational shifts in the healthcare …

Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …

Tabular data is one of the most commonly used types of data in machine learning. Despite
recent advances in neural nets (NNs) for tabular data, there is still an active discussion on …

Given a long list of anomaly detection algorithms developed in the last few decades, how do
they perform with regard to (i) varying levels of supervision,(ii) different types of anomalies …

Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial
Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and …

Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …

The interdisciplinary field of knowledge discovery and data mining emerged from a
necessity of big data requiring new analytical methods beyond the traditional statistical …

Due to the digitization and Internet of Things revolutions, the present electronic world has a
wealth of cybersecurity data. Efficiently resolving cyber anomalies and attacks is becoming a …

Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …

Floods are a devastating natural calamity that may seriously harm both infrastructure and
people. Accurate flood forecasts and control are essential to lessen these effects and …