Diagnostic analysis of cancer based on machine learning

Abstract

Cancer, as the second leading cause of death in the world, caused an estimated 9.6 million deaths in 2018, accounting for one-sixth of all deaths. Early detection and early treatment is the best solution for cancer, and now, through machine learning methods, we can achieve accurate judgment of cancer so as to realize precise treatment and reduce the mortality rate of cancer. During this discussion, we will focus on the applications of machine learning methods to diagnose breast cancer, prostate cancer, oral cancer, which use machine learning methods including neural convolutional networks, K-clustering, support vector machine (SVM), and so on. As of now, machine learning has achieved better results than other methods, but due to the importance and complexity of cancer diagnosis and the cost of human computational capacity for diagnosis, we still hope to find a more accurate and effective method to realize the accurate judgment of cancer, and then introduce it into real-life applications.