Intelligent Paradigms for Healthcare Enterprises: Systems Thinking

• Publisher: Springer
• Year: 2005
• Tongue: English
• Leaves: 261
• Series: Studies in Fuzziness and Soft Computing
• Edition: 1
• Category: Library

✦ Synopsis

This compendium brings together leading researchers in the fields of Intelligent Systems and healthcare aiming at medical engineers, healthcare managers and computer scientists worldwide. This book is an overview of intelligent paradigms and strategic investments that might payoff for the healthcare enterprise. Specifically, the reader will get ideas for efficiency enhancements for improving effectiveness and quality of care and for increasing patient safety. ''Advanced Intelligent Paradigms in Healthcare'' straddles technologic topics from DNA processing and automating medical second opinions in the lab, to telemedicine and chat spaces for rural patient outreach, among many others. In terms of management concerns, this book also explores systems approaches such as automated clinical guidelines, institutional workflow management, and best practices and lessons learned with actual applications.

✦ Table of Contents

Fuzzy Probability and Statistics......Page 3
Contents......Page 6
1.1 Introduction......Page 13
1.2 Notation......Page 15
1.4 Figures......Page 16
1.6 References......Page 17
2.2 Fuzzy Sets......Page 19
2.3 Fuzzy Arithmetic......Page 23
2.4 Fuzzy Functions......Page 25
2.5 Ordering Fuzzy Numbers......Page 29
2.6 References......Page 30
3.2 Fuzzy Probabilities from Confidence Intervals......Page 32
3.3 Fuzzy Probabilities from Expert Opinion......Page 34
3.4 Restricted Fuzzy Arithmetic......Page 35
3.5 Fuzzy Probability......Page 43
3.6 Fuzzy Conditional Probability......Page 47
3.7 Fuzzy Independence......Page 49
3.8 Fuzzy Bayes’ Formula......Page 51
3.9 Applications......Page 52
3.10 References......Page 59
4.2 Fuzzy Binomial......Page 61
4.3 Fuzzy Poisson......Page 64
4.4 Applications......Page 67
4.5 References......Page 70
5.2 Fuzzy Uniform......Page 71
5.3 Fuzzy Normal......Page 73
5.4 Fuzzy Negative Exponential......Page 75
5.5 Applications......Page 77
5.6 References......Page 84
6.2 Fuzzy Estimation......Page 85
6.3 Fuzzy Estimator of μ......Page 86
6.4 References......Page 89
7.1 Fuzzy Estimator of μ......Page 90
7.2 References......Page 92
8.1 Fuzzy Estimator of p......Page 93
8.2 References......Page 95
9.2 Biased Fuzzy Estimator......Page 96
9.3 Unbiased Fuzzy Estimator......Page 97
9.4 References......Page 101
10.2 Fuzzy Arrival Rate......Page 102
10.3 Fuzzy Service Rate......Page 104
10.4 References......Page 106
11.2 Fuzzy Estimators......Page 107
11.3 References......Page 111
12.2 Maximum Entropy Principle......Page 112
12.3 Imprecise Side-Conditions......Page 116
12.4 Summary and Conclusions......Page 118
12.5 References......Page 119
13.2 Max Entropy: Discrete Distributions......Page 120
13.3 Max Entropy: Imprecise Side-Conditions......Page 121
13.5 References......Page 128
14.1 Introduction......Page 130
14.2 Max Entropy: Probability Densities......Page 131
14.4 E = [0,M]......Page 132
14.5 E = [0,∞)......Page 140
14.6 E = (−∞,∞)......Page 144
14.8 References......Page 145
15.2 Non-Fuzzy Case......Page 147
15.3 Fuzzy Case......Page 148
15.4 One-Sided Tests......Page 152
15.5 References......Page 153
16.2 Crisp Case......Page 154
16.3 Fuzzy Model......Page 155
16.4 References......Page 160
17.2 Non-Fuzzy Test......Page 161
17.3 Fuzzy Test......Page 162
17.4 References......Page 164
18.2 Crisp Hypothesis Test......Page 165
18.3 Fuzzy Hypothesis Test......Page 166
18.4 References......Page 168
19.2 Crisp Results......Page 169
19.3 Fuzzy Theory......Page 170
19.4 References......Page 172
20.1 Introduction......Page 173
20.2 Fuzzy Estimators......Page 174
20.3 References......Page 177
21.1 Prediction......Page 178
21.2 References......Page 180
22.2 Tests on a......Page 181
22.3 Tests on b......Page 183
22.4 References......Page 185
23.1 Introduction......Page 186
23.2 Fuzzy Estimators......Page 187
23.3 References......Page 191
24.1 Prediction......Page 192
24.2 References......Page 194
25.2 Tests on b......Page 195
25.3 Tests on c......Page 197
25.4 References......Page 199
26.2 Crisp Hypothesis Test......Page 200
26.3 Fuzzy Hypothesis Test......Page 201
26.4 References......Page 204
27.2 Crisp Hypothesis Tests......Page 205
27.3 Fuzzy Hypothesis Tests......Page 207
27.4 References......Page 213
28.2 Crisp Estimator for the Median......Page 214
28.3 Fuzzy Estimator......Page 215
28.4 Reference......Page 216
29.1 Introduction......Page 217
29.2 Random Fuzzy Numbers......Page 218
29.3 Tests for Randomness......Page 219
29.4 Monte Carlo Study......Page 224
29.5 References......Page 227
30.2 SOLVER......Page 229
30.3 Maple......Page 231
30.4 References......Page 245
31.1 Summary......Page 246
31.2 Future Research......Page 247
31.3 References......Page 249
Index......Page 250
List of Figures......Page 257
List of Tables......Page 260