Machine-learned biomarker identifies those at high risk for liver cancer

Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the journal Proceedings ...

Rejuvenating neurons found to restore learning and memory

Memories are thought to be stored in sparse groups of neurons called engrams. These are the cells that switch on during learning and can later switch on again during recall. In physiological aging and ...
eLife

Dynamics of sensorimotor plasticity during spatial finger augmentation

This study provides a useful contribution to understanding how wearable augmentation devices interact with human proprioception, using a longitudinal design over a single session. Results demonstrate ...
IEEE

Branch-and-Bound Compressive Learning and Reconstruction of Hyperspectral Data With Deep Tucker Decomposition Using Spatial–Spectral Learning Network

Abstract: Hyperspectral imaging (HSI) produces high-dimensional data characterized by detailed spectral and spatial information for each pixel, which is instrumental in applications such as object ...
IEEE

Cluster-guided contrastive learning with masked autoencoder for spatial domain identification based on spatial transcriptomics

Abstract: Recent advancements in spatial transcriptomics technology have enabled the capture of gene expression profiles while maintaining spatial information. Accurately identifying spatial ...

AI Must Master Spatial Intelligence To Fully Operate In The Real World

Spatial intelligence, a frontier technology, is essential for AI to enable humanoids and autonomous vehicles to operate in the physical world.