An immune network inspired evolutionary algorithm for the diagnosis of Parkinson's disease

Stephen L. Smith*, Jon Timmis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (SciVal)

Abstract

This paper presents a novel evolutionary algorithm inspired by protein/substrate binding exploited in enzyme genetic programming (EGP) and artificial immune networks. The immune network-inspired evolutionary algorithm has been developed in direct response to an application in clinical neurology, the diagnosis of Parkinson's disease. The inspiration for, and implementation of the algorithm is described and its performance to the application area considered.

Original languageEnglish
Pages (from-to)34-46
Number of pages13
JournalBioSystems
Volume94
Issue number1-2
DOIs
Publication statusPublished - Oct 2008

Keywords

  • Artificial immune systems
  • Evolutionary algorithms
  • Immune networks
  • Parkinson's disease
  • Biological Evolution
  • Models, Theoretical
  • Algorithms
  • Computer Simulation
  • Humans
  • Computational Biology/methods
  • Immune System Phenomena
  • Parkinson Disease/diagnosis

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