Smart problem solving environment for medical decision support

ABSTRACT

This paper presents a medical problem solving environment (PSE) designed for modelling, simulation, and optimisation of clinical cancer chemotherapy. In order to find optimal chemotherapeutic treatments, two population-based evolutionary algorithms -- Genetic Algorithms and Particle Swarm Optimisation -- have been applied, which can use web services and grid computing to evaluate potential solutions in a distributed and customizable manner. The versatility and robustness of these algorithms make the suggested problem solving environment scalable and adaptable to other problem domains.

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INDEX TERMS

Primary Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.6 Optimization
          Subjects: Constrained optimization

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Heuristic methods
  I.6 SIMULATION AND MODELING
      I.6.7 Simulation Support Systems
          Subjects: Environments

  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES
      Subjects: Medical information systems

General Terms:
Algorithms, Design, Experimentation

Keywords:
cancer chemotherapy, evolutionary algorithms, medical decision support, problem solving environments, web services