A research team led by Prof. Hai Li from the Hefei Institutes of Physical Science, Chinese Academy of Sciences, has become the first to systematically explore how large language models (LLMs) can assist in predicting liver cancer treatment responses—offering a new path toward AI-powered precision medicine.
A research team led by Prof. LI Hai from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, has developed a new model that can accurately predict lung motion caused by breathing, offering safer and more precise options for lung biopsies and radiotherapy.
A research team led by Prof. SHENG Zhigao from the High Magnetic Field Laboratory, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, in collaboration with Prof. A.V. Kimel from Radboud University, has demonstrated that strong magnetic fields can effectively regulate laser-induced ultrafast demagnetization in a two-dimensional van der Waals (vdW) ferromagnet.
A research team led by Prof. HUANG Xiaoqiang from Nanjing University has achieved a major breakthrough in the field of asymmetric electroenzymatic catalysis, developing a novel non-natural dynamic kinetic oxidation system by integrating ferrocene methanol-mediated anodic oxidation with thiamine diphosphate (ThDP)-dependent enzyme catalysis.
Recently, a research team led by Prof. XIE Pinhua from the Hefei lnstitutes of Physical Science of the Chinese Academy of Sciences, has developed a novel prediction model for surface ozone concentration in the North China Plain (NCP) and Yangtze River Delta (YRD) regions. The model is based on a CNN-LSTM framework that integrates spatiotemporal meteorological features, addressing key limitations in existing forecasting methods.