Abstract: Cartesian Genetic Programming (CGP) is now attracting considerable recognition as an evolutionary algorithm that not only delivers high performance, but one that has a representation that is flexible and easy to adapt to a range of applications. Problems based in medicine stand to benefit greatly due their diverse and highly non-linear nature, which can exploit this flexibility. This chapter aims to give an overview of the types of medical problems that may be addressed and illustrates this by considering in detail, a number of published case examples. Finally, for EC practitioners, some advice on the common pit falls, benefits and rewards of medical applications and, specifically, obtaining patient data is offered at the end of the chapter.
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