Steering clustering of medical data in a Self-Enforcing Network (SEN) with a cue validity factor

A Self-Enforcing Network (SEN), which is a self-organized neural network, is introduced to cluster medical data. In addition, a cue validity factor is defined, which affects the clustering of the data. The results show that a user can influence the clustering of data by SEN, thus allowing the analysis of the data depending on economical, medical or nursing interests. The described prototype includes concrete examples and shows the potential of such a network for the analysis of complex data.

I. Introduction

Clustering of medical data means to deal with several problems at once. On the one side, a very large number of clustering algorithms are at disposal (e.g. [1]–[3]), on the other side, the medical data are increasing and the technical problems dealing with such big data are still a major challenge [e.g.] [4].