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. 2023 Sep 15;12(1):234.
doi: 10.1038/s41377-023-01271-7.

Early cancer detection by SERS spectroscopy and machine learning

Lingyan Shi  1 , Yajuan Li  2 , Zhi Li  2
Affiliations

Early cancer detection by SERS spectroscopy and machine learning

Lingyan Shi et al. Light Sci Appl. .

Abstract

A new approach for early detection of multiple cancers is presented by integrating SERS spectroscopy of serum molecular fingerprints and machine learning.

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Figures

Fig. 1
Fig. 1. Schematic of SERS-AICS workflow.
Serum samples were used for label-free SERS spectrum detection enhanced by silver (Ag) nanowires. After the dimensionality reduction of covariance matrix of high-dimensional serum spectral data, cancer-related dimension database of bond level can be obtained. Support vector machine algorithm was then used for classification. Figure is modified from ref.
See this image and copyright information in PMC

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