Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …

Recent improvements in the Internet of Things (IoT) have allowed healthcare to evolve
rapidly. This article summarizes previous studies on IoT applications in healthcare. A …

We present a comprehensive analysis of all ring systems (both heterocyclic and
nonheterocyclic) in clinical trial compounds and FDA-approved drugs. We show 67% of …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …

Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in
infected tissues, the architecture and composition of which are thought to affect disease …

Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in
solving various optimization problems, but their performance may deteriorate drastically …

The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

Clustering is a fundamental machine learning task, which aim at assigning instances into
groups so that similar samples belong to the same cluster while dissimilar samples belong …

Graph neural networks (GNNs) have made rapid developments in the recent years. Due to
their great ability in modeling graph-structured data, GNNs are vastly used in various …