Evolutionary computation in medicine: An overview

Carlos Andrés Peña-Reyes, Moshe Sipper

Research output: Contribution to journalArticlepeer-review

118 Scopus citations

Abstract

The term evolutionary computation encompasses a host of methodologies inspired by natural evolution that are used to solve hard problems. This paper provides an overview of evolutionary computation as applied to problems in the medical domains. We begin by outlining the basic workings of six types of evolutionary algorithms: genetic algorithms, genetic programming, evolution strategies, evolutionary programming, classifier systems, and hybrid systems. We then describe how evolutionary algorithms are applied to solve medical problems, including diagnosis, prognosis, imaging, signal processing, planning, and scheduling. Finally, we provide an extensive bibliography, classified both according to the medical task addressed and according to the evolutionary technique used. Copyright (C) 2000 Elsevier Science B.V.

Original languageEnglish
Pages (from-to)1-23
Number of pages23
JournalArtificial Intelligence in Medicine
Volume19
Issue number1
DOIs
StatePublished - 1 May 2000
Externally publishedYes

Keywords

  • Evolutionary computation
  • Genetic algorithms
  • Medical applications

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Evolutionary computation in medicine: An overview'. Together they form a unique fingerprint.

Cite this