Volume 31, Issue 3 (IJIEPR 2020)                   IJIEPR 2020, 31(3): 379-386 | Back to browse issues page


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venkata appaji S, Shiva Shankar R, Murthy K, Someswara Rao C. Breast Cancer Disease Prediction With Recurrent Neural Networks (RNN). IJIEPR. 2020; 31 (3) :379-386
URL: http://ijiepr.iust.ac.ir/article-1-1069-en.html
1- 1Department of CSE, KKR & KSR Institute of Technology and Sciences, Guntur, A.P, INDIA , venkataappaji.sangapu@gmail.com
2- 2. Department of CSE, S.R.K.R Engineering College, Bhimavaram, W.G. District, A.P. India
Abstract:   (1127 Views)
Cancer is a consortium of diseases which comprises abnormal increase in cells growth by having potential to occupy and attack the entire body. According to study breast cancer is the most likely occurs in the women and which became the second biggest cause of women death. Due to its wide spread and importance some of the researchers work on this, but still there is a need to improvement. During this work in order to partially fulfill this proposed technique of deep learning along with RNN in predicting breast cancer disease which will help the doctor while diagnosis the patient. To assess the efficiency of the proposed method we used breast cancer data belong to UC Irvine repository. Precision, recall, accuracy and f1 score of proposed method shows good scores and proposed technique performs well Consortium
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Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2020/05/3 | Accepted: 2020/05/3 | Published: 2020/05/3

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