Abstract
Neural networks and genetic programming have long since helped humans in diagnoses and treatment of human diseases. However, not much has been done for man’s best friend—the canine’s. This paper thus aims to explore and find the possibility of building software which is based on the use of neural network and Cartesian genetic programming to diagnose the various diseases of canine population. During the study, its outcomes were also compared and contrasted with the results of a neural network combined with simple genetic programming-based system, the results of which confirmed the high success rate of neural network training when it is modified with Cartesian genetic programming for the use of diagnosis of various categories of canine diseases.
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Mahapatra, C. (2018). Medical Diagnosing of Canine Diseases Using Genetic Programming and Neural Networks. In: Panigrahi, B., Hoda, M., Sharma, V., Goel, S. (eds) Nature Inspired Computing. Advances in Intelligent Systems and Computing, vol 652. Springer, Singapore. https://doi.org/10.1007/978-981-10-6747-1_22
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DOI: https://doi.org/10.1007/978-981-10-6747-1_22
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