One of the biggest challenges in managing AAA and PAD is the unpredictability of disease progression. For instance, while ...

All of the state-of-the-art Deep Learning (DL ... based Expectation Maximization (EM) learning for full deployment optimization. We conduct multiple in-sample and out-of-sample experiments to ...

Binding authority works particularly well for smaller, more homogeneous risks. In Munich Re Specialty’s case, the portfolio consists of non-admitted homeowners, small commercial package and ...

In recent years, methods for seismic velocity model building (VMB) based on the nonlinear mapping capabilities of deep learning have been emerging ... through numerical experiments on both homogeneous ...

Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and ...

For the retrospective study, an ensemble 3D U-Net deep learning model was trained for lung tumor detection and segmentation using 1,504 CT scans with 1,828 segmented lung tumors. The model was ...

In a new study published in Science, a Belgian research team explores how genetic switches controlling gene activity define ...

In recent years, Large Language Models (LLMs) have significantly redefined the field of artificial intelligence (AI), ...

DeepSeek’s reliance on reinforcement learning allows the model to use less data and a fraction of the computing power than ...

Research scientists in Switzerland have developed and tested a robust AI model that automatically segments major anatomic structures in MRI images, independent of sequence. In the study, the model ...