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NEURAL NETWORK ANALYSIS FOR TUMOR INVESTIGATION AND CANCER PREDICTION
Author(s) -
T. Vijayakumar
Publication year - 2019
Publication title -
journal of electronics and informatics
Language(s) - English
Resource type - Journals
ISSN - 2582-3825
DOI - 10.36548/jes.2019.2.004
Subject(s) - artificial neural network , convolutional neural network , computer science , recurrent neural network , artificial intelligence , cancer , breast cancer , process (computing) , machine learning , deep learning , set (abstract data type) , medicine , programming language , operating system
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.

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