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S<scp>E</scp>RS‐Based Biosensors Combined with Machine Learning for Medical Application**

Yan Ding, Yang Sun, Cheng Liu, Qiao‐Yan Jiang, Feng Chen, Yue Cao

2023ChemistryOpen90 citationsDOIOpen Access PDF

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.

Topics & Concepts

Computer scienceSurface-enhanced Raman spectroscopyNanotechnologyBiosensorMachine learningRaman spectroscopyArtificial intelligenceBiochemical engineeringMaterials scienceRaman scatteringEngineeringPhysicsOpticsBiosensors and Analytical DetectionSpectroscopy Techniques in Biomedical and Chemical ResearchGold and Silver Nanoparticles Synthesis and Applications
S<scp>E</scp>RS‐Based Biosensors Combined with Machine Learning for Medical Application** | Litcius