ISSNIP

A Hybrid Data Mining Approach for Knowledge Extraction and Classification in Medical Databases

Investigators
Staff:

Brijesh Verma;
Post Doctoral Research Fellow: Rinku Panchal.

Student: Peter McLeod, Syed Zahid Hassan, Hong Lee.
Collaborations

Abdesselam Bouzerdoum;
Arcot Sowmya;
Stuart Crozier;
Svetha Venkatesh.

Description
Introduction: This project aims to study a novel hybrid data mining approach which is an effective combination of statistical and intelligent techniques in conjunction with a neural fusion, in order to utilize the strengths of each individual technique and compensate for each other?s weaknesses.
Significance: More specifically, this project presents a novel hybrid data mining approach for knowledge extraction and classification in medical databases.
Applications:
Challenges: The approach combines various clustering techniques such as self organizing map, k-means, etc. with a neural network based data fusion. The idea is to cluster all data in soft clusters using neural and statistical clustering and fuse them using serial and parallel fusion in conjunction with a neural classifier.
Publication
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