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1 | (10) |
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Uncertainty versus Precision in Biomedicine and Epidemiology |
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1 | (2) |
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3 | (1) |
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4 | (1) |
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Fuzzy Logic in Biomedicine and Epidemiology |
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5 | (3) |
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8 | (1) |
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9 | (2) |
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Basic Concepts of Fuzzy Sets Theory |
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11 | (30) |
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11 | (3) |
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Operations with Fuzzy Sets |
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14 | (9) |
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Triangular Norms and Conorms |
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20 | (2) |
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22 | (1) |
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Fuzzy Sets and Membership Functions |
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23 | (7) |
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Properties and Characteristics of Fuzzy Sets |
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27 | (2) |
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29 | (1) |
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Extension Principle and Fuzzy Numbers |
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30 | (7) |
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Zadeh Extension Principle |
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30 | (2) |
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32 | (2) |
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Arithmetic Operations on Fuzzy Numbers |
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34 | (3) |
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37 | (4) |
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Composition of Fuzzy Relations |
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38 | (3) |
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41 | (18) |
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Statistical Models in Epidemiology |
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42 | (2) |
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Mathematical Models in Epidemiology |
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44 | (13) |
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The Reproduction of an Infection |
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44 | (3) |
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47 | (7) |
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Computer Simulation Models |
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54 | (3) |
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57 | (2) |
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Probability, Possibility and Fuzzy Events |
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59 | (20) |
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Probability and Fuzzy Measures |
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60 | (7) |
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60 | (1) |
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61 | (1) |
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62 | (4) |
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Probability/Possibility Transformations Applied to the Prostate Cancer Analysis |
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66 | (1) |
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67 | (7) |
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67 | (1) |
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67 | (5) |
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Fuzzy Expected Value Applied to the Accidents of Traffic Analysis, in the Sao Paulo City, Brazil |
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72 | (2) |
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Probability of Fuzzy Events |
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74 | (4) |
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Fuzzy Probabilities of Epidemic Events |
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76 | (2) |
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78 | (1) |
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Fuzzy Logic and Risk Estimators |
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79 | (18) |
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Risk and Common Measures of Association Used in Epidemiology |
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79 | (3) |
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80 | (2) |
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Infectious Diseases and Violation of the Stability Assumption |
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82 | (3) |
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83 | (2) |
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Measures of Association for Non-observable Subsets of the Target Population |
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85 | (6) |
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Randomization and Baseline Transmission |
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87 | (4) |
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Fuzzy Logic and Risk Estimators |
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91 | (6) |
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Fuzzy Conditional Probability |
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91 | (1) |
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Fuzzy Measures of Association |
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92 | (5) |
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Fuzzy Decision Making in Public Health Strategies |
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97 | (14) |
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Designing a Vaccination Strategy |
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98 | (4) |
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The Measles Epidemic in Sao Paulo |
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102 | (1) |
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The Impact of the Vaccination |
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103 | (8) |
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Forecasting and Projection Models |
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104 | (1) |
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The Case of the Measles Epidemic in Sao Paulo |
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105 | (6) |
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Fuzzy Rule-Based Models in Epidemiology |
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111 | (40) |
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112 | (3) |
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115 | (2) |
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Inference Procedure in Fuzzy Rule-Based Models |
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117 | (5) |
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122 | (3) |
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123 | (1) |
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123 | (1) |
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124 | (1) |
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Some Types of Fuzzy Rule-Based Models |
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125 | (8) |
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126 | (3) |
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The Takagi-Sugeno-Kang Model |
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129 | (2) |
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The Standard Additive Model |
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131 | (2) |
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Modeling Health Decisions through Fuzzy Linguistic Systems |
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133 | (18) |
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A Fuzzy Model for HIV Natural History |
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133 | (7) |
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A Fuzzy Model to Estimate the Risk of Neonatal Death |
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140 | (5) |
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A Fuzzy Model to Quality of Life Evaluation |
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145 | (6) |
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Fuzzy Rule-Based Dynamical Models |
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151 | (30) |
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The Fuzzy Rule Dynamic Structure |
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152 | (2) |
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A Model for Canine Rabies Seroprevalence |
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154 | (13) |
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A TSK Model for Canine Rabies |
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156 | (5) |
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A Mamdani Model for Canine Rabies |
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161 | (6) |
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A Fuzzy Dynamical Model for a SIR Epidemic |
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167 | (6) |
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A Fuzzy Linguistic Dynamical Model Based on the Extension Principle |
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173 | (8) |
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Dealing with the Opinions of Experts |
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174 | (1) |
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The Extension Principle Methodology Applied in the Canine Rabies Study |
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175 | (6) |
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Fuzzy Dynamical Systems in Epidemic Modeling |
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181 | (26) |
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181 | (2) |
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183 | (3) |
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Epidemiology with Heterogeneity |
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186 | (16) |
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187 | (9) |
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196 | (6) |
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Fuzzy Differential Inclusion |
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202 | (5) |
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The SI Fuzzy Model by Fuzzy Differential Inclusion |
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202 | (5) |
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Classical Dynamical Systems with Fuzzy Rule-Based Parameters |
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207 | (18) |
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Fuzzy Modeling in Symptomatic a HIV Infected Population |
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208 | (11) |
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Classical HIV/AIDS Models |
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208 | (4) |
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A Fuzzy Rule-Based Model to Estimate |
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212 | (5) |
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Fuzzy Expectancy of Symptomatic Individuals and Real Data |
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217 | (2) |
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Fuzzy Model to Compute the Life Expectancy of HIV Infected Individuals |
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219 | (6) |
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The Influence of AIDS on the Mortality Rate |
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220 | (1) |
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Average Number and the Life Expectancy of Individuals |
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221 | (4) |
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225 | (28) |
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The Classical Reed-Frost Model |
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225 | (2) |
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The Stochastic Reed-Frost Model |
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227 | (12) |
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The Probabilistic Structure |
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229 | (9) |
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238 | (1) |
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239 | (3) |
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The Possibilistic Structure |
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240 | (1) |
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241 | (1) |
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242 | (7) |
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249 | (4) |
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Hybrid Models in Epidemiology |
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253 | (24) |
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A Fuzzy Model for the Estimation of Optimal Age for Vaccination Against Measles |
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255 | (14) |
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A Bayesian Approach to Fuzzy Hypotheses Testing |
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256 | (2) |
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Estimating the Optimal Age to Vaccinate Against Measles |
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258 | (5) |
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263 | (5) |
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268 | (1) |
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A Fuzzy Model to Study a Predator-Prey Dynamics |
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269 | (8) |
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270 | (1) |
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270 | (1) |
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Formulation of the Predator-Prey Fuzzy Model |
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271 | (2) |
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Fitting the Holling-Tanner Model |
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273 | (3) |
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276 | (1) |
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...and Beyond: Fuzzy Logic in Medical Diagnosis |
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277 | (34) |
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278 | (1) |
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Computer Models and Expert Systems for Medical Diagnosis |
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279 | (8) |
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Mathematical Models in Medical Diagnosis |
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279 | (5) |
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The Stanford Certainty Factor Algebra |
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284 | (1) |
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Expert Systems for Medical Diagnosis |
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284 | (3) |
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287 | (24) |
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Fuzzy Relations Diagnostic Models |
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289 | (2) |
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Fuzzy Cluster Analysis Models |
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291 | (1) |
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Smets' Model for Fuzzy Diagnosis |
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292 | (2) |
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Bellamy's State-Space Approach |
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294 | (3) |
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Other Fuzzy Diagnostic Systems |
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297 | (9) |
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Hybrid Diagnostic Systems |
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306 | (5) |
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311 | (2) |
References |
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313 | (22) |
Index |
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335 | |