Intelligent Cyber-Physical Systems typically utilize sensors to gather a significant amount of raw data which often possesses temporal and high-dimensional characteristics. Ensuring the data ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

GREmLN leverages a graph-based architecture to represent gene-gene interactions to predict cell behavior for therapeutic ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

In response to these challenges, we developed a novel Spatial Graph Neural Network (SGNN) model to predict motor learning outcomes from electroencephalogram (EEG) data using the spatial-temporal ...