Application of serum Raman spectroscopy combined with classification model for rapid breast cancer screening

• DOI: 10.3389/fonc.2023.1258436
• Publication Date: 2023-10-27T00:23:37Z
• Authors: Runrui Lin; Bowen Peng; Lintao Li; Xiaoliang He; Huan Yan; Chao Tian; Huaichao Luo; Gang Yin
• Keywords: Diagnostic model; Gold standard (test)

This study aimed to evaluate the feasibility of using general Raman spectroscopy as a method screen for breast cancer. The objective was develop machine learning model that utilizes detect serum samples from cancer patients, benign cases, and healthy subjects, with puncture biopsy gold standard comparison. goal explore value in differential diagnosis cancer, lesions, individuals.In this study, blood were collected total 333 participants. Among them, there 129 cases tumors (pathologically diagnosed labeled cancer), 91 lesions benign), 113 controls (labeled normal). spectra each group collected. To classify normal, benign, sample groups, principal component analysis (PCA) combined support vector (SVM) used. SVM evaluated cross-validation method.The results revealed significant differences mean between normal tumor/benign groups. Although showed slight variations achieved remarkable prediction accuracy up 98% classifying groups.In conclusion, exploratory has demonstrated tremendous potential clinical adjunctive diagnostic rapid screening tool