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Volume-3 | Issue-3

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Volume-3 | Issue-3

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Comparative Analysis an Early Fault Diagnosis Approaches in Rotating Machinery by Convolution Neural Network
Volume-3 | Issue-2

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Volume - 1 | Issue - 2 | december 2019

NEURAL NETWORK ANALYSIS FOR TUMOR INVESTIGATION AND CANCER PREDICTION
Pages: 89-98
Published
December, 2019
Abstract

Predicting the category of tumors and the types of the cancer in its early stage remains as a very essential process to identify depth of the disease and treatment available for it. The neural network that functions similar to the human nervous system is widely utilized in the tumor investigation and the cancer prediction. The paper presents the analysis of the performance of the neural networks such as the, FNN (Feed Forward Neural Networks), RNN (Recurrent Neural Networks) and the CNN (Convolutional Neural Network) investigating the tumors and predicting the cancer. The results obtained by evaluating the neural networks on the breast cancer Wisconsin original data set shows that the CNN provides 43 % better prediction than the FNN and 25% better prediction than the RNN.

Keywords

Cancer Diagnosis Cancer Prediction Tumor Investigation Neural Networks Improved Performance

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