|Smith, Stephen L. / Cagnoni, Stefano (Hrsg.)|
Genetic and Evolutionary Computation
2010. 250 Seiten, Hardcover
ISBN 978-0-470-74813-8 - John Wiley & Sons
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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 analyse 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 Inhalt
About the Editors
List of Contributors
2. Evolutionary Computation: A Brief Overview
3. A Review of Medical Applications of Genetic and Evolutionary Computation
4. Applications of GEC in Medical Imaging
4.1. Evolutionary Deformable Models for Medical Image Segmentation
Chris McIntosh and Ghassan Hamarneh
4.2. Feature Selection for the Classification of Microcalcifications in Digital Mammograms using Genetic Algorithms, Sequential Search and Class Separability
Santiago E. Conant-Pablos, Rolando R. Hernández-Cisneros and Hugo Terashima-Marin
4.3. Hybrid Detection of Features within the Retinal Fundus using a Genetic Algorithm
Vitoantonio Bevilacqua, Lucia Cariello, Simona Cambò, Domenico Daleno and Giuseppe Mastronardi
5. New Analysis of Medical Data Sets using GEC
5.1. Genetic Programming for Exploring Medical Data using Visual Spaces
Julio J. Valdés, Alan J. Barton and Robert Orchard
5.2. An Interactive Search for Rules in Medical Data Using Multiobjective Evolutionary Algorithms
Daniela Zaharie, Diana Lungeanu and Flavia Zamfirache
5.3. Analysis of Mammography Reports using Maximum Variation Sampling
Robert M. Patton, Barbara G. Beckerman and Thomas E. Potok
6. Advanced Modelling, Diagnosis and Treatment using GEC
6.1. Towards an Alternative to Magnetic Resonance Imaging for Vocal Tract Shape Measurement using the Principles of Evolution
David M Howard, Andy M Tyrrell and Crispin Cooper
6.2. The Objective Assessment of Visuo-spatial Ability using Implicit Context Representation Cartesian Genetic Programming
Michael A. Lones and Stephen L. Smith
6.3. How Genetic Algorithms can improve Pacemaker Efficiency
Laurent Dumas and Linda El Alaoui
7. The Future for Genetic and Evolutionary Computation in Medicine: Opportunities, Challenges and Rewards
Appendix. Introductory Books and Useful Links