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  • "Knowledge and Data" Driven AIGC in Brain Image Computing for Alzheimer's Disease Analysis

    A research team led by Prof. WANG Shuqiang from the Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences introduced a Prior-Guided Adversarial Learning with Hypergraph (PALH) model for predicting abnormal connections in Alzheimer's disease.

    Jan 20, 2024
  • Artificial Intelligence Facilitates Tissue Substructure Identification from Spatial Resolved Transcriptomics

    A research team led by Prof. ZHANG Shihua from the Academy of Mathematics and Systems Science has proposed a new computational tool, STAGATE, to decipher tissue substructures from spatial resolved transcriptomics. The model uses artificial intelligence technology to integrate spatial location information and gene expression profile of spatial spots. In this algorithm, a graph attention autoencoder is introduced, with a graph attention mechanism in the middle hidden layer, which can learn the heterogeneous similarities between neighboring spots adaptively.

    Apr 02, 2022
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Information Tech
  • Researchers Using SDGSAT-1 to Monitor Offshore Oil and Gas Flaring

    Researchers from the Aerospace Information Research Institute of the Chinese Academy of Sciences leveraged the advanced capabilities of SDGSAT-1's Glimmer Imager and Thermal Infrared Spectrometer to monitor gas flaring activities in the South China Sea.

    Jan 20, 2025
  • Researchers Develop Transformer-powered Graph Machine Learning Model to Predict Cancer Genes

    A research team from the Xinjiang Institute of Physics and Chemistry of CAS proposed a graph machine learning model, namely TREE, based on the Transformer framework. With this novel Transformer-based architecture, TREE not only identifies the most influential omics data type but also detects the most representative network paths involved in regulating genes that drive cancer formation and progression.

    Jan 21, 2025
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