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 ...

A new study tested how humans and ChatGPT understand color metaphors, revealing key differences between lived experience and language-based AI.

Recent studies on integrating multiple omics data highlighted the potential to advance our understanding of the cancer disease process. Computational models based on graph neural networks and ...

This important study presents a new method for longitudinally tracking cells in two-photon imaging data that addresses the specific challenges of imaging neurons in the developing cortex. It provides ...

Existing GNNs usually conduct the layer-wise message propagation via the ‘full’ aggregation of all neighborhood information which are usually sensitive to the structural noises existed in the graphs, ...