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Machine Learning Predicting Optimal Preparation of Silica-Coated Gold Nanorods for Photothermal Tumor Ablation.

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第一作者： Jintao,Zhang

第一单位： State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-sen University, Guangzhou 510275, China.

作者： Jintao,Zhang ^[1] ; Jinchang,Yin ^[2] ; Ruiran,Lai ^[1] ; Yue,Wang ^[1] ; Baorui,Mao ^[1] ; Haonan,Wu ^[1] ; Li,Tian ^[3] ; Yuanzhi,Shao ^[4]

作者单位： State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-sen University, Guangzhou 510275, China. ^[1] State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-sen University, Guangzhou 510275, China.;Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China. ^[2] State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China. ^[3] State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics, Sun Yat-sen University, Guangzhou 510275, China.;Guangdong Provincial Key Laboratory of Magnetoelectric Physics and Devices, Sun Yat-sen University, Guangzhou 510275, China. ^[4]

关键词 high-throughput prediction machine learning photothermal tumor ablation process optimization silica-coated gold nanorods

DOI 10.3390/nano13061024

PMID 36985918

发布时间 2024-09-15

基金项目

62005322,61975244/National Natural Science Foundation of China 2022A1515010006,2020A1515010426/Guangdong Basic and Applied Basic Research Foundation 2021qntd27,19lgpy272/Fundamental Research Funds for the Central Universities 2019M653174/National Postdoctoral Research Foundation of China

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Machine Learning Predicting Optimal Preparation of Silica-Coated Gold Nanorods for Photothermal Tumor Ablation.

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