TY  - JOUR
AU  - Sankaradass, Veeramalai 
AU  - Arputharaj, Kannan 
PY  - 2011
TI  - A Descriptive Framework for the Multidimensional Medical Data Mining and Representation
JF  - Journal of Computer Science
VL  - 7
IS  - 4
DO  - 10.3844/jcssp.2011.519.525
UR  - https://thescipub.com/abstract/jcssp.2011.519.525
AB  - Problem statement: Association rule mining with fuzzy logic was explored by research for
effective datamining and classification. Approach: It was used to find all the rules existing in the
transactional database that satisfy some minimum support and minimum confidence constraints. Results:
In this study, we propose new rule mining technique using fuzzy logic for mining medical data in order
to understand and better serve the needs of Multidimensional Breast cancer Data applications.
Conclusion: The main objective of multidimensional Medical data mining is to provide the end user with
more useful and interesting patterns. Therefore, the main contribution of this study is the proposed and
implementation of fuzzy temporal association rule mining algorithm to classify and detect breast cancer
from the dataset.