Fuzzy Systems in MedicinePiotr S. Szczepaniak, Paulo J.G. Lisboa Provides an introduction to the fundamental concepts of fuzziness together with a compilation of recent advances in the application to medicine. The tutorials in the first part of the book range from basic concepts through theoretical frameworks to rule simplification through data clustering methodologies and the design of multivariate rule bases through self-learning by mapping fuzzy systems onto neural network structures. The case studies which follow are representative of the wide range of applications currently pursued in relation to medicine. The majority of applications presented in this book are about bridging the gap between low-level sensor measurements and intermediate or high-level data representations. The book offers a comprehensive perspective from leading authorities world-wide and provides a tantalising glimpse into the role of sophisticated knowledge engineering methods in shaping the landscape of medical technology in the future. |
Contents
J Kacprzyk | 29 |
E Straszecka | 48 |
Fuzzy Sets and Knowledge Representation | 78 |
Baczyński J Drewniak | 112 |
Bruha P Berka | 137 |
R Babuška | 172 |
W Pedrycz | 202 |
Entropy and Energy Measures of Fuzziness in ECG Signal Processing | 227 |
Fusion of Numerical and Structural Image Information | 429 |
Bloch | 445 |
A Bardossy A Blinowska | 466 |
ClosedLoop Control of Anaesthesia Using Fuzzy Logic | 467 |
A Linkens M F Abbod J K Backory J S Shieh | 484 |
Fuzzy Inference Neural Networks and Their Applications to Medical | 503 |
NeuroFuzzy Modelling of Heart Rate Signals and Application | 519 |
Fuzzy Diagnosis by ScoreBased Tests Implementation Issues | 543 |
Fuzzy Logic System for ECG Interpretation | 246 |
EEG Analysis for Assessment of Depth of Anaesthesia | 261 |
Fuzzy Sets in Medical Image Processing | 281 |
G Berks D G v Keyserlingk | 316 |
H R Tizhoosh G Krell B Michaelis | 335 |
F Masulli A Schenone A M Massone | 351 |
P R Innocent R I John M Barnes | 394 |
F Waidelich H Eichfeld R Graumann | 410 |
A Comparison of Fuzzy Decision Models Supporting | 561 |
Fuzzy and Crisp Logical Rule Extraction Methods in Application | 592 |
W Duch R Adamczak K Grąbczewski G Zal Y Hayashi | 617 |
R Molitor C B Tresp | 636 |
The Development of a Fuzzy Expert System for the Analysis of Umbilical | 652 |
Garibaldi E C Ifeachor | 669 |
| 693 | |
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Common terms and phrases
anaesthesia analysis application approach artery c-means classification clinical clustering algorithm concept corresponding crisp data set decision defined defuzzification denoted detection diagnosis disease distance domain edge detection elements entropy evaluation example expert system fractal frequency fuzzy clustering fuzzy control fuzzy expert system fuzzy implications fuzzy inference neural fuzzy logic fuzzy membership fuzzy numbers fuzzy rules fuzzy set theory Fuzzy Systems heart rate variability IEEE image processing infusion input interpretation interval knowledge base knowledge representation linguistic variables machine learning matrix measure of fuzziness medical image membership degrees membership functions membership values method module neural models neuro-fuzzy neuron node normal object obtained optimization output parameters partition patient performance pixel possible problem procedure propofol QRS complex represent representation rule-based samples scores segmentation signal simulation structure subsets Table techniques threshold Type vectors voxel weights Zadeh