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.
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