Rapid and efficient screening of human papillomavirus by Raman spectroscopy based on GA-SVM

Abstract In this study, a rapid, noninvasive and efficient screening method for human papillomavirus (HPV) was proposed by combining cervical secretion Raman spectral data with a pattern recognition algorithm. We measured the cervical secretion Raman spectra of 58 HPV positive and 196 HPV negative samples. The preliminary assignment of the Raman peaks in the measured cervical secretion spectra indicated changes in specific biomolecules between the groups, and we analyzed them according to their differences. The specificity of the airPLS-PLS-GA-SVM model was 100%, the sensitivity was 94.4%, and the total accuracy was 98.6%. The results show that the combination of cervical secretion Raman spectroscopy and multivariate statistical analysis has great potential in the early screening of HPV and the samples of low-level lesions and high-level lesions were preliminarily classified effectively, providing a basis for the design of computer-aided diagnosis systems in the future.