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Genetic and evolutionary computation : medical applications / edited by Stephen Smith, Stefano Cagnoni. — Oxford : Wiley, 2011. – (61.038/G328) |
Contents
Contents
About the Editors
List of Contributors
1 Introduction
2 Evolutionary Computation: A Brief Overview
2.1 Introduction
2.2 Evolutionary Computation Paradigms
2.3 Conclusions
3 A Review of Medical Applications of Genetic and Evolutionary Computation
3.1 Medical Imaging and Signal Processing
3.2 Data Mining Medical Data and Patient Records
3.3 Clinical Expert Systems and Knowledge-based Systems
3.4 Modelling and Simulation of Medical Processes
3.5 Clinical Diagnosis and Therapy
4 Applications of GEC in Medical Imaging
4.1 Evolutionary Deformable Models for Medical Image Segmentation: A Genetic Algorithm Approach to Optimizing Learned， Intuitive， and Localized Medial-based Shape Deformation
4.2 Feature Selection for the Classification of Microcalcifications in Digital Mammograms using Genetic Algorithms， Sequential Search and Class Separability
4.3 Hybrid Detection of Features within the Retinal Fundus using a Genetic Algorithm
5 New Analysis of Medical Data Sets using GEC
5.1 Analysis and Classification of Mammography Reports using Maximum Variation Sampling
5.2 An Interactive Search for Rules in Medical Data using Multiobjective Evolutionary Algorithms
5.3 Genetic Programming for Exploring Medical Data using Visual Spaces
6 Advanced Modelling， Diagnosis and Treatment using GEC
6.1 Objective Assessment of Visuo-spatial Ability using Implicit Context Representation Cartesian Genetic Programming
6.2 Towards an Alternative to Magnetic Resonance Imaging for Vocal Tract Shape Measurement using the Principles of Evolution
6.3 How Genetic Algorithms can Improve Pacemaker Efficiency
7 The Future for Genetic and Evolutionary Computation in Medicine: Opportunities， Challenges and Rewards
7.1 Opportunities
7.2 Challenges
7.3 Rewards
7.4 The Future for Genetic and Evolutionary Computation in Medicine
Appendix: Introductory Books and Useful Links
Index
