Name
Title | ||
|---|---|---|
Neural network with classification based on multiple association rule for classifying mammographic data |
Abstract | ||
|---|---|---|
Breast cancer is the second leading cause of cancer deaths in women today and the most common cancer among women. At present there is no known method to prevent breast cancer but early detection increase the chance of cure. Screening mammograms is considered as the best tool for doctors to detect breast cancer at an early stage. In this paper we present the application of Classification based on multiple association rule (CMAR) in neural network (NN) to classify breast cancer mammographic data. CMAR is used in the initial step in creating structure of neural network. It is tested on the real datasets: Mammography Mass Data from UCI repository. |
Year | Venue | Keywords |
|---|---|---|
2009 | IDEAL | cancer death,breast cancer,initial step,breast cancer mammographic data,neural network,multiple association rule,early stage,uci repository,mammography mass data,common cancer,best tool,artificial neural network,medical diagnosis,association rule |
Field | DocType | Volume |
Early detection,Mammography,Data mining,Pattern recognition,Breast cancer,Computer science,Association rule learning,Artificial intelligence,Artificial neural network,Machine learning,Cancer,Medical diagnosis | Conference | 5788 |
ISSN | ISBN | Citations |
0302-9743 | 3-642-04393-3 | 1 |
PageRank | References | Authors |
0.40 | 12 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benaki Lairenjam | 1 | 1 | 0.40 |
| Siri Krishan Wasan | 2 | 35 | 6.76 |