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

Rosas, Francisco Javier Luna and Romo, Julio Cesar Martínez and Vargas, Marco Antonio Hernández and Reyes, Claudio Frausto (2021) Automatic Detection of Breast Cancer Based on Raman Spectroscopy Using a Neuro-Fuzzy Approach. In: Highlights on Medicine and Medical Science Vol. 6. B P International, pp. 37-50. ISBN 978-93-91312-43-5

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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.

Item Type: Book Section
Subjects: Grantha Library > Medical Science
Depositing User: Unnamed user with email support@granthalibrary.com
Date Deposited: 30 Oct 2023 05:22
Last Modified: 17 Jun 2024 06:45
URI: http://asian.universityeprint.com/id/eprint/1680

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