Title :
High-dimensional data structure analysis using Self-Organising Maps
Author :
Hodych, Oles ; Nikolski, Iouri ; Pasichnyk, Volodymyr ; Shcherbyna, Yuri
Abstract :
In this article the authors discuss several approaches to high dimensional data structure analysis using self-organising maps. The described approaches utilise graphical images for the purpose of data structure interpretation. The evaluation of the discussed techniques has been performed using the real medical data from cardiology. The research, results of which are outlined in this paper, is a continuation of the earlier work related to the analysis of the same medical data.
Keywords :
cardiology; data structures; data visualisation; image classification; medical image processing; neural net architecture; self-organising feature maps; artificial neural networks; cardiology medical data; data classification; data clustering; data structure interpretation; data visualisation; graphical images; high dimensional data structure analysis; self-organising maps; Biomedical imaging; Cardiology; Data analysis; Data structures; Decision making; Information systems; Lattices; Medical diagnostic imaging; Neural networks; Neurons; artificial neural networks; classification; clustering; data visualisation; diagnostics;
Conference_Titel :
CAD Systems in Microelectronics, 2007. CADSM '07. 9th International Conference - The Experience of Designing and Applications of
Conference_Location :
Lviv-Polyana
Print_ISBN :
966-533-587-0
DOI :
10.1109/CADSM.2007.4297529
