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.
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