Classification for early diagnosis for breast cancer base on Neural Network

뉴럴네트워크 기반의 유방암 조기 진단을 위한 분류

  • Received : 2017.10.11
  • Accepted : 2017.12.20
  • Published : 2017.12.28


Breast cancer is the sccond most female cancer patient in the entire female cancer patient, and has emerged as the highest contributor to female cancer deaths. If breast cancer id detected early, the cure rate is 92 percent. However, if early detection fails, breast cancer has a very high rate of metastasis. The transition from cancer to cancer has become more successful as cancer progresses. Early diagnosis of cancer is an important factor in improving quality of life. Examples of breast cancer include Mammograph, ultrasound, and Momotome. Mommography is not only painful for the examiner, but also for easy access to breast cancer exam inations. In this paper, breast cancer diagnosis data mammograph data was used. In addition, the Neural Network were classified for early diagnosis of breast cancer early using NEWFM. After learning of data using NEWFM, the accuracy of the breast cancer data classification was 84.4391%.


Neural Network;Classification;Breast Cancer;Mammography;Cancer Detection


Supported by : 장안대학교


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