A.E. Yankovskaya, D.V. Galkin, and G.E. Chernogoryuk (Russia)
Computer visualisation, cognitive graphic tools, applied intelligent systems, N-M multiterminal networks, medical diagnostics.
Authors analyze cognitive graphics (CG) as an
instrument for computer visualization in applied
intelligent systems. Three approaches to CG design are
described: matrix based, naturalistic and based on N-M
multiterminal networks (the original authors approach).
Practical application of N-M multiterminal networks
(N-MMN) is presented for knowledge base
representation, revealing regularities and decision
making and decision justification in medical diagnostics
(lung deceases). Authors suggest that combining matrix
based, naturalistic and N-MMN methods of CG
knowledge representation we design complex and
effective CG tool box for AIS.