Associative Classifiers for Medical Images

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.

• Type: Conference
• Year: 2002
• Where: KDD
• Authors: Alexandru Coman, Maria-Luiza Antonie, Osmar R. Zaïane
• Keywords: Accurate Data Mining, Data Cleaning Phase, Data Mining, KDD 2002, Pre-processing Phase