A STUDY ON EARLY PREVENTION AND DETECTION OF BREAST CANCER USING THREE-MACHINE LEARNING TECHNIQUES
Nafees Akhter Farooqui, Ritika Ritika · International Journal of Advanced Research in Computer Science · 2018
The size of the Medical data repositories is increasing rapidly. Thus, we cannot easily analyze these data for finding the valuable and hidden knowledge. There are several machine learning techniques that are used for medical analysis. Breast cancer is the most common cancer particularly diagnosed in women. It is one of the leading causes of death worldwide. Only early detection can prevent the breast cancer’s mortality. Breast cancer is a cancer that forms in the cells of the breasts. Now a days Breast cancer had become a very major disease not only in India but also in other countries. The main objective of this paper is to early diagnosis of the breast cancer patients. For early prevention and detection of the breast cancer patients, three machine learning techniques (i.e. Decision tree, Support Vector Machine, Random Forest) are used, that also eliminates the waiting time and reducing the human and technical errors in diagnosing the breast cancer. Earlier detection of Breast Cancer gives more lives and falling the death rate. Its cure rate and expectation depend on the early identification and finding of the infections. The selection of suitable machine learning technique is a challenge for the diagnosis of breast cancer. Thus, we have created a model for a breast cancer prediction system to analyze risk levels which help in prognosis. This paper becomes very helpful to doctor for diagnosis breast cancer and helpful to patients for early treatment.