Colon Cancer Prediction based on Artificial Neural Network

1. Md. Asaduzzaman Sabuj

Colon Cancer Prediction based on Artificial Neural Network

1. Md. Asaduzzaman Sabuj * § Lead Engineer

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§ Chittagong University of Engineering and Technology

Colon Cancer Prediction based on Artificial Neural Network

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CSTP888B

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Abstract

Artificial neural networks (ANNs) consists of computational neurons or processing elements are linear mathematical model which abstract away the complex biological model and its aim is good, human like predictive ability. Artificial intelligence tries to simulate some properties of biological neural networks. In this study on the basis of previous dataset the in symptoms data are applied to a supervised back propagation artificial neural network learning process to find out the predictive outcome which is better than logistic regression (LR) process. As in most cases ANN is an adaptive system that changes its structure on the basis of internal and external information, the predictive result is more accurate than any other processes.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

1. Md. Asaduzzaman Sabuj. 2013. "Colon Cancer Prediction based on Artificial Neural Network". Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 13 (GJCST Volume 13 Issue G3).

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GJCST Volume 13 Issue G3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Artificial Neural Network back propagation colon cancer prediction supervised learning

Classification

GJCST-G Classification F.1.1

Submission ReceivedDecember 8, 2012
Peer Review Double Blind
Handling Editor
Accepted January 2, 2013
Published January 15, 2013

Version of record

v1.2

Issue date

September 28, 2013

Language

English

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Article Matrices

Total Score: 142

Country: Bangladesh

Subject: Global Journal of Computer Science and Technology

Authors: 1. Md. Asaduzzaman Sabuj, Priyam Biswas (PhD/Dr. count: 0)

View Count (all-time): 441

Total Views (Real + Logic): 3442

Total Downloads (simulated): 310

Publish Date: 2013 01, Tue

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Total Views: 3.4K

Total Downloads: 310

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