Deep Neural Network Design and Implementation for Predicting Malignancy of Cancer Tumors

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Abstract

Breast cancer is the most frequent cancer among women after lung cancer. It is second popular cause of death in the world. Breast cancer cells usually form a tumor (abnormal tissue).There are two types of breast cancer tumors: those that are non-cancerous, or ‘benign’, and those that are cancerous, which are ‘malignant’. Early detection of cancer tumors can prevent its mortality and can take respective precautions according to the type of cancer tumor (either it is benign or malignant). The main objective of this paper is to early diagnosis of the malignancy of cancer tumors which helps to decrease the death rate and helps to give more lives. The selection of suitable deep learning technique is a challenge for the diagnosis of breast cancer. So we created model for prediction of malignancy of cancer tumors using neural network to analyze risk levels that helps in prognosis. It is useful for a doctor to predict the stage of cancer and take respective precautions

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Priya*, J. G., Satyanjani, K. S., … Prakash, K. B. (2019). Deep Neural Network Design and Implementation for Predicting Malignancy of Cancer Tumors. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 7845–7847. https://doi.org/10.35940/ijrte.d5399.118419

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