Prognosis and Diagnosis of Breast Cancer Using Interactive Dashboard Through Big Data Analytics

Author(s): Gomathi N, and Sandhya P

Background: Cancer is a life threatening disease of present scenario among which breast cancer is the second highly mortal disease in women. There are several stages of cancer and an early detection of breast cancer can reduce the mortality rate. The primary detection of breast cancer is mammography due to the naked eye prediction of the disease by radiologist, they suggest for the next level of diagnosis like MRI, PET or biopsy. These tests are time consuming and not cost effective. In this work, we aim for an interactive dashboard methodology to determine the presence or absence of a distinct mass called tumor in mammographic image. Here we also tend to confirm the mass to be benign or malignant by analyzing the shape of the mass using image processing techniques. We also predict a possibility to determine the stages of breast cancer using big data and cloud as a next level to the computer aided method of cancer detection. Methodology: In this paper, we also use Backpropagation and Support vector machine system (SVM) for analysis of benign or malignant cancer, we can also predict the stage of cancer using mammographic images. Conclusion: The results performed in nntraintool determine the performance rate, training state, regression and error histogram of the test image. And the cloud and big data analysis idea suggest to a next level of home level cancer stage prediction.

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