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Medical Applications of Evolutionary Computation

Stephen L. Smith
A senior lecturer in the Department of Electronics
University of York, UK.


The use of evolutionary computation in real-world applications is becoming widespread, but examples in medicine and healthcare less so, due to the special challenges this area presents. The aim of this tutorial is to give a practical guide to applying evolutionary computation to medicine and healthcare, by considering two case examples in detail, the diagnosis of Parkinson's disease and the detection of breast cancer.

Outline of the contents

The tutorial will consider the following theoretical and practical aspects of the application of EC to medicine: i) Introduction to medical applications of EC and how these differ from other real-world applications ii) Overview of past work in the from a medical and EC point of view iii) Two case examples of medical applications in depth iv) Practical advice on how to get started working on medical applications, including existing medical datasets and conducting new medical studies and protecting intellectual property. v) Summary, further reading and links



Stephen L. Smith is currently a senior lecturer in the Department of Electronics at the University of York, UK. His main research interests are in developing novel representations of evolutionary algorithms with application to problems in medicine. His work is currently centered on the diagnosis of neurological dysfunction and analysis of mammograms. He is associate editor for the journal Genetic Programming and Evolvable Machines and a member of the editorial board for the International Journal of Computers in Healthcare and Neural Computing Applications. He has some 75 refereed publications, is a Chartered Engineer, a fellow of the British Computer Society and currently holds a Royal Academy of Engineering Enterprise Fellowship.


The length of the tutorial:
two hours.


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