Learn how to build your own GPT-style AI model with this step-by-step guide. Demystify large language models and unlock their ...

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

Scientists at UCSF combined advanced brain-network modeling, genetics, and imaging to reveal how tau protein travels through ...

A sneeze. Ocean currents. Smoke. What do these have in common? They're instances of turbulence: unpredictable, chaotic, ...

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

However, the high-dimensional complexity of spatiotemporal phenomena makes these models difficult to interpret. This paper proposes a river network feature identification architecture based on coupled ...

Using brain gene expression maps from the Allen Human Brain Atlas, the researchers tested the degree to which Alzheimer’s risk genes explain the patterns of both actual and residual tau. This allowed ...

A new brain imaging study suggests that people who report symptoms of addiction to short-form video platforms—such as TikTok ...

AI is everywhere. From the massive popularity of ChatGPT to Google cramming AI summaries at the top of its search results, AI ...

High-resolution flow field data are essential for accurately evaluating the aerodynamic performance of aircraft. However, acquiring such data via ...

In this study, we propose a Virtual network-based Diffusion Convolutional Recurrent Neural Network (V-DCRNN) for estimating unobserved speed data in urban traffic networks using a virtual network.

It’s been recognized for some time that Alzheimer’s disease affects brain regions differently and that tau — a protein known to misbehave — plays an important role in the disease. Normally, tau helps ...