S e RS‐Based Biosensors Combined with Machine Learning for Medical Application **
Abstract: Surface‐enhanced Raman spectroscopy (SERS) has shown strength in non‐invasive, rapid, trace analysis and has been used in many fields in medicine. Machine learning (ML) is an algorithm that can imitate human learning styles and structure existing content with the knowledge to effectively improve learning efficiency. Integrating SERS and ML can have a promising future in the medical field. In this review, we summarize the applications of SERS combined with ML in recent years, such as the recognition of biological molecules, rapid diagnosis of diseases, developing of new immunoassay techniques, and enhancing SERS capabilities in semi‐quantitative measurements. Ultimately, the possible opportunities and challenges of combining SERS with ML are addressed.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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S e RS‐Based Biosensors Combined with Machine Learning for Medical Application ** ; volume:12 ; number:1 ; year:2023 ; extent:13
ChemistryOpen ; 12, Heft 1 (2023) (gesamt 13)
- Creator
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Ding, Yan
Sun, Yang
Liu, Cheng
Jiang, Qiao‐Yan
Chen, Feng
Cao, Yue
- DOI
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10.1002/open.202200192
- URN
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urn:nbn:de:101:1-2023011114153678849405
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:32 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Ding, Yan
- Sun, Yang
- Liu, Cheng
- Jiang, Qiao‐Yan
- Chen, Feng
- Cao, Yue