Hasil Pencarian - Boneng Mao

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  1. 1
    A novel rhodamine B fluorescence probe for rapid identification of different amino acids by high efficiency fluorescence spectrum-mass spectrometry

    A novel rhodamine B fluorescence probe for rapid identification of different amino acids by high efficiency fluorescence spectrum-mass spectrometry oleh Xiujie Duan, Tao Jin, Boneng Mao, Shihe Shao, Lei Zhao

    Diterbitkan 2024-09-01
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  2. 2
    Polymeric nanomaterials encapsulating fluorescent polyindole-nido- carborane: design, synthesis and biological evaluation

    Polymeric nanomaterials encapsulating fluorescent polyindole-nido- carborane: design, synthesis and biological evaluation oleh Jia Cao, Tao Jin, Shihe Shao, Boneng Mao, Jin Feng

    Diterbitkan 2024-07-01
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  3. 3
    Oil-in-water strategy coating Curcumin-nido-Carborane fluorescent complex with acrylic resins for cell imaging

    Oil-in-water strategy coating Curcumin-nido-Carborane fluorescent complex with acrylic resins for cell imaging oleh Chen Lu, Zhendong Yao, Jiankang Feng, Boneng Mao, Guofan Jin

    Diterbitkan 2023-08-01
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  4. 4
    Construction and Multicenter Diagnostic Verification of Intelligent Recognition System for Endoscopic Images From Early Gastric Cancer Based on YOLO-V3 Algorithm

    Construction and Multicenter Diagnostic Verification of Intelligent Recognition System for Endoscopic Images From Early Gastric Cancer Based on YOLO-V3 Algorithm oleh Zhendong Yao, Zhendong Yao, Tao Jin, Boneng Mao, Bo Lu, Yefei Zhang, Sisi Li, Weichang Chen

    Diterbitkan 2022-01-01
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  5. 5
    Communication molecules (ncRNAs) mediate tumor-associated macrophage polarization and tumor progression

    Communication molecules (ncRNAs) mediate tumor-associated macrophage polarization and tumor progression oleh Min Yao, Min Yao, Xuhua Mao, Zherui Zhang, Feilun Cui, Shihe Shao, Shihe Shao, Boneng Mao

    Diterbitkan 2024-03-01
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  6. 6
    Multi-center verification of the influence of data ratio of training sets on test results of an AI system for detecting early gastric cancer based on the YOLO-v4 algorithm

    Multi-center verification of the influence of data ratio of training sets on test results of an AI system for detecting early gastric cancer based on the YOLO-v4 algorithm oleh Tao Jin, Yancai Jiang, Boneng Mao, Xing Wang, Bo Lu, Ji Qian, Hutao Zhou, Tieliang Ma, Yefei Zhang, Sisi Li, Yun Shi, Yun Shi, Zhendong Yao

    Diterbitkan 2022-08-01
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