Automated Breast Cancer Diagnosis Based on Machine Learning Algorithms

Breast cancer is the main reason for mortality in women. It was very difficult to predict breast cancer in the early stages by doctors and pathologists. They need some automated tools to make an early prediction of cancer and diagnosis as soon as possible. Some research found that Machine learning (ML) algorithm helps them to take decisions and perform diagnosis based on data collected by the medical field. In this paper, we use various ML algorithms and classifiers like KNearestNeighbors (KNN), Support Vector Machine (SVM) and Random Forest (RF) to find the accurate result of cancer in less intervals of time. It has been found that Support Vector Machine has highest accuracy 98.83% and Random Forest has second highest accuracy with 98.24% among all other models.