In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

In the last few years, the trend in health care of embracing artificial intelligence (AI) has
dramatically changed the medical landscape. Medical centres have adopted AI applications …

The rapid progress in digitalization and automation have led to an accelerated growth in
healthcare, generating novel models that are creating new channels for rendering treatment …

Ensemble learning combines several individual models to obtain better generalization
performance. Currently, deep learning architectures are showing better performance …

Today's healthcare data management systems are facing key challenges in terms of data
transparency, traceability, immutability, audit, data provenance, flexible access, trust …

The emergence of smart cities and sustainable development has become a globally
accepted form of urbanization. The epitome of smart city development has become possible …

The Internet of Things confers seamless connectivity between people and objects, and its
confluence with the Cloud improves our lives. Predictive analytics in the medical domain can …

The rapid growth and adaptation of medical information to identify significant health trends
and help with timely preventive care have been recent hallmarks of the modern healthcare …

Deep learning methods have achieved significant results in various fields. Due to the
success of these methods, many researchers have used deep learning algorithms in …

Accurate detection of traffic accidents as well as condition analysis are essential to
effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be …