SERS-Based Biosensors Combined with Machine Learning for Medical Application** |
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Authors: | Yan Ding Yang Sun Cheng Liu Qiao-Yan Jiang Prof?Dr Feng Chen Dr Yue Cao |
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Institution: | Department of Forensic Medicine, Nanjing Medical University, Nanjing, 211166 P.R. China |
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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. |
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Keywords: | chemometrics machine learning medicine Raman spectroscopy statistical spectral analysis |
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