Associative Classifiers for Medical Images
- Maria-Luiza Antonie, Dept. of Computing Science UofA
- Osmar R. Zaiane, University of Alberta (Database)
- Alexandru Coman
This paper presents two classification systems for medical images based on association rule mining. The system we propose consists of: a pre-processing phase, a phase for mining the resulted transactional database, and a final phase to organize the resulted association rules in a classification model. The experimental results show that the method performs well, reaching over 80% in accuracy. Moreover, this paper illustrates how important the data cleaning phase is in building an accurate data mining architecture for image classification.
Citation
M. Antonie, O. Zaiane, A. Coman. "Associative Classifiers for Medical Images". Lecture Notes in Artificial Intelligence, 2797, pp 68-83, January 2003.| Keywords: | |
| Category: | In Journal |
BibTeX
@article{Antonie+al:LNCS03,
author = {Maria-Luiza Antonie and Osmar R. Zaiane and Alexandru Coman},
title = {Associative Classifiers for Medical Images},
Volume = "2797",
Pages = {68-83},
journal = {Lecture Notes in Artificial Intelligence},
year = 2003,
}Last Updated: February 05, 2020Submitted by Sabina P
