Evolutionary computation in medicine: an overview
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 o...
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| Veröffentlicht in: | Artificial intelligence in medicine 2000-05, Vol.19 (1), p.1-23 |
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| container_title | Artificial intelligence in medicine |
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| creator | Peña-Reyes, Carlos Andrés Sipper, Moshe |
| description | 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. |
| doi_str_mv | 10.1016/S0933-3657(99)00047-0 |
| format | Article |
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| ispartof | Artificial intelligence in medicine, 2000-05, Vol.19 (1), p.1-23 |
| issn | 0933-3657 1873-2860 |
| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Algorithms Artificial Intelligence Biological Evolution Computer applications Evolutionary computation Genetic algorithms Genetics Medical applications Medical Informatics Computing Medicine Reviews |
| title | Evolutionary computation in medicine: an overview |
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