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ABSTRACT
Over two decades, the most observed deadliest and dreadful disease is considered to be cancer. The positive rate of cancer and the death rate over the years is rapidly increasing at an alarming rate. Among women, Breast cancer is the most diagnosed cancer. More than the treatment, the initial clinical examination of breast cancer itself is a very painful process for many patients. Even a small mistake can lead to false-negative and false positive results that will be a burden on the life of a patient. To make this task easier and accurate we will be dealing with a novel approach by using technology. However, the
present technology can make this painful clinical examination comparatively easier. This paper presents data mining algorithms like Decision tree, SVM which will be executed in the Spyder(anaconda) platform where the input is taken as values that differentiate the patient’s record whether the cancer tissues are benign or malignant with higher probability based on the training dataset. This project also summarizes the cons of a traditional breast cancer diagnosis.
Keywords – Benign, Cancer, Data Mining, Decision tree, Malignant, SVM, Spyder.
INTRODUCTION
Thousands of females fall victim to breast cancer every year. The human body comprises millions of cells each with its unique function. When there is the unregulated growth of the cells it is termed as cancer. In this, cells divide and grow uncontrollably, forming an abnormal swelling tissue part called a tumor. Tumor cells grow and invade digestive, nervous and circulatory systems disrupting the bodies’ normal functioning. Though every single tumor is not cancerous. Cancer is classified by the type of cell that
is affected and more than 200 types of cancers are known. This paper is focused on Breast cancer. Breast cancer is the most common type of cancer among females across the world. As per the National Breast Cancer Foundation, “Breast cancer is the most commonly diagnosed cancer in women”. Breast cancer is the second largest cause of cancer death among women. Women generally approach clinics with a mild to serious pain in their breasts. After the examination of the breasts, the doctors usually suggest an ultrasound scan. The proceedings after the scan are more painful. Some women feel that the pain
is intensely increased only after clinical proceedings. It is because of the painful process that is followed to detect whether the lymph node is malignant or benign. Malignant tumors are harmful or cancerous and benign tumors are harmless and can be removed through surgery. The treatment is then decided after thoroughly examining the state of the tumor. With the help of this paper, the detection of the state of the tumor can be decided with the help of data mining algorithms.
