Matching hidden non-markovian models: Diagnosing illnesses based on recorded symptoms

ESM 2010 - 2010 European Simulation and Modelling Conference

Volumn , Issue , 2010, Pages 133-138

  Krull, Claudia ^a   Buchholz, Robert ^a   Horton, Graham ^a  

^a OTTO VON GUERICKE UNIVERSITY   (Germany)

Author keywords

Decision support systems; Health care; Markov chain; Stochastic; Time series analysis

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS; DIAGNOSIS; HEALTH CARE; MARKOV PROCESSES; MODAL ANALYSIS; TIME SERIES ANALYSIS;

APPLICATION EXAMPLES; DISCRETE STOCHASTIC MODELS; MARKOV-CHAIN; PARTIALLY OBSERVABLE SYSTEMS; SIMULATION ALGORITHMS; STOCHASTIC; SYSTEM CONFIGURATIONS; TECHNICAL PROCESS;

COMPUTER SIMULATION;

EID: 84874688023     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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3. Bramer M., 2008. Principles of Data Mining. Springer-Verlag London ltd.
4. Buchholz R.; Krull C; Strigl T.; and Horton G., 2010. Using Hidden non-Markovian Models to Reconstruct System Behavior in Partially-Observable Systems. In 3rd International ICST Conference on Simulation Tools and Techniques.
5. Fink G.A., 2008. Markov Models for Pattern Recognition. Springer, Berlin, Heidelberg.
6. Horton G., 2002. A New Paradigm for the Numerical Simulation of Stochastic Petri Nets with General Firing Times. In Proceedings of the European Simulation Symposium 2002. SCS European Publishing House, 129-136.
7. Krull C. and Horton G., 2009. HIDDEN NON-MARKOVIAN MODELS: FORMALIZATION AND SOLUTION APPROACHES. In Proceedings of 6th Vienna Conference on Mathematical Modelling, Vienna, Austria. 682-693.
8. Lazarova-Molnar S., 2005. The Proxel-Based Method: Formalìsation, Analysis and Applications. Ph.D. thesis, Otto-von-Guericke-University Magdeburg.