Utilizing machine learning to expedite the fabrication and biological application of carbon dots
文献信息
发布日期
2023-11-01
DOI
10.1039/D3MA00443K
影响因子
0
作者
Peide Zhu, Rongye Zhu, Juncheng Wang
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摘要
As a novel type of nanomaterial, carbon dots (CDs) are widely used in biology owing to their optical property, biocompatibility, and intrinsic theranostic properties. Taking advantage of these features, the CDs serve as color agents, fluorescence probes, and anti-cancer drugs. Machine learning (ML) has progressed dramatically, especially for widespread use in the biological field. In this review, we introduce the ML workflow and the leading models in the process and then demonstrate the application of CDs in bioimaging, biosensing, and cancer treatment. Next, we generalize the use in the development of CDs’ combination of ML in complementary aspects. Finally, we briefly summarize the challenges and expectations for the future. This review provides new thoughts and guidance for CDs on the application and integration of machine learning.
期刊推荐
New Journal of Chemistry
Russian Journal of Bioorganic Chemistry
Acta Materialia
Russian Chemical Bulletin
Current Opinion in Colloid & Interface Science
Russian Journal of Applied Chemistry
Saudi Pharmaceutical Journal
Crystallography Reports
Russian Journal of Organic Chemistry
Russian Journal of General Chemistry
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