Addressing this issue, researchers from Germany have developed a geometric deep learning model that can better preserve geometric information and inter-pixel relationships when analyzing CT-P scans.

A geometric neural net for dynamic data Traditional deep learning is not suited to understanding dynamic systems that change regularly as a function of time, like firing neurons or flowing fluids.

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

As reported in their study published in the Journal of Medical Imaging, the team built a geometric deep learning model called "Graph Fully-Convolutional Network" (GFCN).

A research team from Leipzig University, the Max Planck Institute and Heidelberg University, all in Germany, devised a new segmentation algorithm for stroke lesions that improves upon previous methods ...

The tool, called Deep Predictor of Binding Specificity (DeepPBS), is a geometric deep learning model designed to predict protein–DNA binding specificity from protein–DNA complex structures.

Symbolica recently co-authored a paper with Google DeepMind on “ categorical deep learning,” which mathematically demonstrated how its approach could supersede previous work on geometric deep ...