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Serum SERS spectroscopy combined with classification algorithm in the non-destructive identification of cervical cancer

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Abstract

Gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) were used as substrates in combination with a low-concentration serum surface-enhanced Raman spectroscopy (SERS) detection scheme to obtain spectral signals from healthy individuals and cervical cancer patients. The best principal component scores were selected by principal component analysis (PCA) combined with linear discriminant analysis (LDA) and support vector machine (SVM) to analyze the spectral differences distinguishing healthy and cervical cancer patients. The accuracy of the two models was 97.9% and 96.9%, respectively. SERS technique based on Au NPs/785 PSi PhCs has great potential to improve the screening of cervical cancer.

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Acknowledgements

This work was supported by the Science and Technology Foundation of Guizhou Province (QKHJ[2020]1Y259); the United Foundation of Zunyi City and Zunyi Normal Collage (ZSKHHZ272); the Natural Science Foundation of Xinjiang Uygur Autonomous Region (PT2302).

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Authors and Affiliations

  1. Physics and Chemistry Analysis Center, Xinjiang University, Urumqi, 830046, China

    Ningning Gao, Jun Tang & Tao Wang

  2. College of Physics and Technology, Xinjiang University, Urumqi, 830046, China

    Qing Wang

  3. College of Software, Xinjiang University, Urumqi, 830046, China

    Xiaoyi Lv

  4. College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, China

    Hongmei Li & Xiaxia Yue

  5. School of Physics and Electronic Science, Zunyi Normal College, Guizhou, 563006, China

    Furu Zhong

  6. College of Chemical Engineering, Xinjiang University, Urumqi, 830046, China

    Jihong Fu

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  1. Ningning Gao
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  2. Qing Wang
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  3. Jun Tang
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  4. Xiaoyi Lv
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Contributions

NG: conceptualization and roles/writing—original draft and writing—review and editing; QW: investigation; JT: methodology, data curation, validation, supervision; XL: visualization; HL: formal analysis; XY: project administration; JF: resources; FZ: funding acquisition; TW: project administration.

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Correspondence to Jun Tang or Furu Zhong.

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Gao, N., Wang, Q., Tang, J. et al. Serum SERS spectroscopy combined with classification algorithm in the non-destructive identification of cervical cancer. Appl. Phys. A 129, 822 (2023). https://doi.org/10.1007/s00339-023-07116-9

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