Deep Convolution Neural Network Based Breast Cancer Bigdata Analysis for Crowd Cloud Sourcing
Rethinakumar1, GopinathGanapathy2, Jeong-Jin Kang3

1Rethinakumar, Assistant Professor, Department of Information and Communication, Dong Seoul University, Korea Research Scholar, Bharathidasan University, India.

2GopinathGanapathy, Registrar, Bharathidasan University, India.

3Jeong-Jin Kang, Professor, Department of Information and Communication, Dong Seoul University, Korea.

Manuscript received on 11 January 2020 | Revised Manuscript received on 07 February 2020 | Manuscript Published on 20 February 2020 | PP: 378-383 | Volume-9 Issue-3S January 2020 | Retrieval Number: C10810193S20/2020©BEIESP | DOI: 10.35940/ijitee.C1081.0193S20

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Abstract: Breast cancer is one of the dangerous diseases leads fast death among women. Several kinds of cancers are affecting people, but breast cancer affects highly women. In medical industry removal of women breasts or major surgery is taken forward as the solution, where it reoccurs after surgery also. Only solution to save women from breast cancer is to identify and detect the earlier stage of cancer and provide necessary treatment. Hence various research works have been focused on finding good solution for diagnosing and classifying the cancer stages as benign, malignant or severe malignant. Still the accuracy of classification needs to be improved on complex breast cancer datasets. Few of the earlier research works have proposed machine learning algorithms, which are semi-automatic and accuracy is also not high. Thus, to provide a better solution this paper aimed to use one of the deep learning algorithms such as Convolution Neural Networks for diagnosing various kinds of breast cancer dataset. From the experimental results, it is obtained that the proposed deep learning algorithms outperforms than the other algorithms.

Keywords: Breast Cancer, Convolution Neural Network, Deep Learning, Diagnosis, Prediction, Benign, Malignant.
Scope of the Article: Cloud Computing