Optimizing Number of Inputs to Classify
Breast Cancer Using Artificial Neural Network |
Bindu Garg1,*, M.M. Sufian Beg2 and A.Q. Ansari3 |
1Department of Computer Science and Information Technology, Institute Of Technology and Management, Sec-23 A, Gurgaon-122017, India, bindusingla@gmail.com |
2Department of Computer Engineering, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025 India, mmsbeg@hotmail.com |
3Department of Electrical Engineering, Jamia Millia Islamia, Jamia Nagar, New Delhi-110025, India, aqansari62@gmail.com |
| *Corresponding author: |
Dr. Bindu Garg,
Department of Computer Science and Information Technology,
Institute Of
Technology and Management, Sec-23 A,
Gurgaon-122017, India,
E-mail : bindusingla@gmail.com |
|
| Received July 07, 2009; Accepted August 25, 2009; Published August 26, 2009 |
Citation: Garg B, Sufian Beg MM, Ansari AQ (2009) Optimizing Number of Inputs to Classify Breast Cancer Using
Artificial Neural Network. J Comput Sci Syst Biol 2: 247-254. doi:10.4172/jcsb.1000037 |
| Copyright: © 2009 Garg B, et al. This is an open-access article distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author
and source are credited. |
| Abstract |
The Objective of this research work is to prove significant role of each attribute to decide breast cancer type
using Computer Aided Diagnosis. One of major challenges in medical domain is the extraction of intelligible knowledge
from medical diagnostic data in minimum time and cost This research shows that out of these attributes
stated, some attributes can be ignored to decide the type Breast Cancer as if the number of inputs are less then it
reduces the time and cost in analyzing the breast cancer. In this paper, significant role of each attribute is proved
by experiment in matlab.
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