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SERS-Based Biosensors Combined with Machine Learning for Medical Application.

Yan DingYang SunCheng LiuQiao-Yan JiangFeng ChenYue Cao
Published in: ChemistryOpen (2023)
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.
Keyphrases
  • raman spectroscopy
  • sensitive detection
  • machine learning
  • gold nanoparticles
  • healthcare
  • label free
  • loop mediated isothermal amplification
  • artificial intelligence
  • deep learning
  • mass spectrometry
  • risk assessment