By integrating large-kernel convolutional blocks and a novel loss function, LKNet effectively addresses challenges such as ...

A new deep learning-based approach has been developed to overcome one of the critical limitations in fluorescence microscopy: severe image degradation caused by noise in dynamic in vivo imaging ...

A research team from Kumamoto University has developed a promising deep learning model that significantly enhances the accuracy of subgraph matching—a critical task in fields ranging from drug ...

Journal Reference: Chi Chen, Shyue Ping Ong. A universal graph deep learning interatomic potential for the periodic table. Nature Computational Science, 2022; 2 (11): 718 DOI: 10.1038/s43588-022 ...

PURPOSEPatients with epithelial ovarian cancer (EOC) have an elevated risk for venous thromboembolism (VTE). To assess the risk of VTE, models were developed by statistical or machine learning ...