Increasing the diversity of medical data mining through distributed object technology.

Data mining has been recently experiencing a boom of interest from researchers and software producers. In medicine, however, its applications are still rather rare. In this paper, we argue that this is primarily due to the requirements of reproducibility of results and diversity of available data mining tools, both of which are crucially important for medical research. We propose to tackle the diversity requirement by means of distributed object technologies. The results presented here rely on our experience with medical data mining using the method GUHA and with further developing that method.