Automatic Detection of Breast Cancer Based on Raman Spectroscopy Using a Neuro-Fuzzy Approach

Abstract

Breast cancer is caused by the presence of malignant cells in the female breast, a sickness that has recently expanded around the globe, not just in Mexico but also in other areas of the world. We provide an automatic Breast cancer classification approach in which a Raman signal is classified as coming from a biopsy of healthy tissue (class w1) or a biopsy of sick tissue  (class w2) ; to do so, we built patterns using Raman spectra accurately quantifying each Raman peak to supply naturally reduced data to a classifier; we used Adaptative Neuro-Fuzzy Inference System (ANFIS) classifier and high rates of correct classification were obtained. This provides essential clinical tools to professionals for the speedy and accurate automatic identification of breast cancer.We believe that our method could be used to treat various types of cancer, such as lung, prostate, and stomach cancers.