Über die Autorin bzw. den Autor

Stephen Smith, Department of Electronics, University of York, UK
Stephen Smith is a senior lecturer within the Department of Electronics at the University of York. His research interests include evolutionary algorithms and assisted clinical diagnosis. He is co-organiser of the annual GECCO (Genetic and Evolutionary Computation Conference), and co-workshop organiser for the Medical Applications of Genetic and Evolutionary Computation Workshop. His editorial experience includes current service as subject area editor for the Journal of Systems Architecture and guest editor for a special issue of the BioSystems journal.

Stefano Cagnoni, Università degli Studi di Parma, Italy
Stefano Cagnoni is an associate professor in the department of computer engineering at the University of Parma. His research interests are in the fields of computer vision, robotics, evolutionary computation and neural networks. He is secretary of the Italian Association for Artificial Intelligence and Co-chairman of EvoIASP, the EvoNet working group on applications of Evolutionary Computation to Image and Signal Processing. He is co-editor of Genetic and Evolutionary Computation for Image Processing and Analysis, soon to publish with Hindawi Press.

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Genetic and Evolutionary Computation: Medical Applications provides an overview of the range of GEC techniques being applied to medicine and healthcare in a context that is relevant not only for existing GEC practitioners but also those from other disciplines, particularly health professionals. There is rapidly increasing interest in applying evolutionary computation to problems in medicine, but to date no text that introduces evolutionary computation in a medical context. By explaining the basic introductory theory, typical application areas and detailed implementation in one coherent volume, this book will appeal to a wide audience from software developers to medical scientists.

Centred around a set of nine case studies on the application of GEC to different areas of medicine, the book offers an overview of applications of GEC to medicine, describes applications in which GEC is used to analyze medical images and data sets, derive advanced models, and suggest diagnoses and treatments, finally providing hints about possible future advancements of genetic and evolutionary computation in medicine.

• Explores the rapidly growing area of genetic and evolutionary computation in context of its viable and exciting payoffs in the field of medical applications.
• Explains the underlying theory, typical applications and detailed implementation.
• Includes general sections about the applications of GEC to medicine and their expected future developments, as well as specific sections on applications of GEC to medical imaging, analysis of medical data sets, advanced modelling, diagnosis and treatment.
• Features a wide range of tables, illustrations diagrams and photographs.

Aus dem Klappentext

Genetic and Evolutionary Computation: Medical Applications provides an overview of the range of GEC techniques being applied to medicine and healthcare in a context that is relevant not only for existing GEC practitioners but also those from other disciplines, particularly health professionals. There is rapidly increasing interest in applying evolutionary computation to problems in medicine, but to date no text that introduces evolutionary computation in a medical context. By explaining the basic introductory theory, typical application areas and detailed implementation in one coherent volume, this book will appeal to a wide audience from software developers to medical scientists.

Centred around a set of nine case studies on the application of GEC to different areas of medicine, the book offers an overview of applications of GEC to medicine, describes applications in which GEC is used to analyze medical images and data sets, derive advanced models, and suggest diagnoses and treatments, finally providing hints about possible future advancements of genetic and evolutionary computation in medicine.

• Explores the rapidly growing area of genetic and evolutionary computation in context of its viable and exciting payoffs in the field of medical applications.
• Explains the underlying theory, typical applications and detailed implementation.
• Includes general sections about the applications of GEC to medicine and their expected future developments, as well as specific sections on applications of GEC to medical imaging, analysis of medical data sets, advanced modelling, diagnosis and treatment.
• Features a wide range of tables, illustrations diagrams and photographs.

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Genetic and Evolutionary Computation

John Wiley & Sons

Chapter One

Genetic and evolutionary computation (GEC) is now attracting considerable interest, since the first algorithms were developed some 30 years ago. Although often regarded as a theoretical pursuit, research and development of a wide range of real-world applications of GEC has long been evident at conferences and in the scientific literature. Medicine and healthcare is no exception and the challenge, and worthy aim, has motivated many to apply GEC to a wide range of clinical problems.

The aim of this book is to provide an overview of the range of GEC techniques being applied to medicine and healthcare, in a context that is supportive not only for existing GEC practitioners, but also for those from other disciplines, particularly health professionals. This encompasses doctors, consultants and other clinicians, as well as those who act in a technical role in the health industry, such as medical physicists, technicians and those who have an interest in learning more with a view to implementing systems or just understanding them better. Consequently, a concise introduction to genetic and evolutionary computation is required, and this has been provided in Chapter 2 for those readers who are not familiar with the more common paradigms of GEC.

It was also felt important that an overview of recent work should be reported as concisely and fully as practically possible, and this has been provided in Chapter 3. The problem with any review is that, despite the best efforts of the author, it is outdated, incomplete and unbalanced as soon as it has been published. It is also impossible to know which papers are going to be of future significance, for the individual or community as a whole, regardless of the subject, author or source of publication. There is also the risk that the review becomes too cumbersome to maintain the reader's interest, comprising an endless list of summaries with little structure or context. For these reasons, this review has adopted two guiding principles. Firstly, it is limited to the last five years of publications, as it is felt that this will encompass very recent approaches and yet previous work of merit will have been refined, extended or combined with other techniques and reported in more recent publications. Secondly, no distinction has been made on the grounds of source of publication, whether it is a journal, conference or workshop presentation. It is anticipated, however, that all papers will have been peer reviewed to provide some level of confidence in the work presented. The overriding aim of the review is to stimulate thought on how techniques investigated to date may be used to the reader's advantage.

The main component of this book is a set of nine case examples on the application of GEC to different areas of medicine, which have been grouped into three chapters covering medical imaging, the analysis of medical data sets, and medical modelling, diagnosis and treatment. This is by no means a representative selection, but one that conveys the breadth of techniques employed. The source of these contributions has been the Genetic and Evolutionary Computation Conference (GECCO) Workshop on Medical Applications of Genetic and Evolutionary Computation (MedGEC), which has been part of GECCO since 2005. The Workshop has provided a valuable venue for reporting work, often in early stages of development, but which has then matured to be published in GEC journals – notable examples are special issues in the journal Genetic Programming and Evolvable Machines and the Journal of Artificial Evolution and Applications.

The final chapter of this book will then consider the future of medical applications of GEC, the opportunities, challenges and rewards that practitioners face.

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