An Optimization Algorithm for Computer-Aided Diagnosis of Breast Cancer Based on Support Vector Machine.

ABSTRACT: As one of the most vulnerable cancers of women, the incidence rate of breast cancer in China is increasing at an annual rate of 3%, and the incidence is younger. Therefore, it is necessary to conduct research on the risk of breast cancer, including the cause of disease and the prediction of breast cancer risk based on historical data. Data based statistical learning is an important branch of modern computational intelligence technology. Using machine learning method to predict and judge unknown data provides a new idea for breast cancer diagnosis. In this paper, an improved optimization algorithm (GSP_SVM) is proposed by combining genetic algorithm, particle swarm optimization and simulated annealing with support vector machine algorithm. The results show that the classification accuracy,

SUBMITTER: Dou Y 

PROVIDER: S-EPMC8287651 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature