Table of Contents
Preface xi
Chapter 1 Medical Sciences in the Age of Synthesis 1
1.1 Professional Practice and Stochastic Medical Reasoning 1
1.1.1 Synthesis in medical sciences 1
1.1.2 Environmental health and geomedicine 5
1.1.3 On ancient Greek and Chinese medicine 9
1.1.4 Decision-making in conditions of in situ uncertainty 12
1.1.5 A brief note on logical thinking in ancient Greece and China 14
1.1.6 Enter stochastic medical reasoning 16
1.2 Health: The Fundamental Roles of Space-Time and Uncertainty 19
1.3 Abstract and Concrete Modes of Thinking 23
1.4 Issues of Sound Medical Decision-Making 25
1.4.1 Key elements of a medical investigation 26
1.4.2 Reflection, recognition primed decision and robust decision methods 30
1.4.3 Algorithmic medical decision-making methods 33
1.4.4 Does expert knowledge translate into expert judgment? 34
1.5 Medical Dialectics and Knowledge Synthesis: An Outline 36
Chapter 2 Reasoning Amidst Uncertainty 39
2.1 When "To Know" Means "To Be Uncertain Of" 39
2.1.1 Common medical reasoning errors 39
2.1.2 Physician's language and metalanguage 42
2.1.3 The notion of knowledge base 44
2.2 The Space-Time Domain of Stochastic Medical Reasoning 47
2.2.1 Location-time coordinates and metric 47
2.2.2 The spatiotemporal random field model 51
2.3 In Situ Logic and Uncertain Mind States 53
2.3.1 How much a health care provider does not know: Ontic and epistemic uncertainty 54
2.3.2 Appreciating case individuality and legal disputes 56
2.3.3 Case communication uncertainty: Entitled to their own opinions but not to their own facts 58
2.3.4 Formal vs. in situ logic 60
2.3.5 From state of nature to state of mind (assertion) 63
2.3.6 Ranking of assertion forms 71
2.3.7 The Three Qs of the triadic case formula 74
2.3.8 Uncertainty factors: A review 76
2.4 SMR's View of Medical Connectives: Beyond Drug Digestion 79
2.4.1 Conversational (dialogical) connective interpretation 80
2.4.2 Content-dependent vs. content-independent connectives 83
2.5 Natural Laws and Scientific Models 85
2.5.1 Infectious disease and human exposure modeling 86
2.5.2 Medical syllogism and the justification of professional assertions 89
2.5.3 Reconstructing Chinese arguments in terms of Greek syllogisms 94
2.5.4 Revisiting content-dependent and content-independent assertions 96
2.6 Substantive Conditionals in Medical Thinking 99
2.6.1 The notion of content-dependent conditional 100
2.6.2 Paradoxes of mainstream logic 105
2.6.3 Conditionals and metalanguage 114
2.6.4 Conditionals and natural laws 117
2.6.5 Over-extending and extrapolating 119
2.7 The Object Language-Metalanguage Connection 121
2.7.1 Relations between states 122
2.7.2 Combinations of medical inferences and derivative assertions 131
2.7.3 Levels of justification and uncertainty 133
2.7.4 Does postmodern decision analysis make sense? 138
Chapter 3 The Role of Probability 141
3.1 How Much Understanding is Sufficient in Medical Investigations? 141
3.1.1 Medical assertions and partial understanding 141
3.1.2 On rationality and belief 144
3.1.3 Knowledge theory revisited: Platonism, context and continuity in medical thinking 145
3.1.4 Concerning medical expertise 147
3.2 Space-Time Probabilities of Medical Cases 148
3.2.1 Common probability interpretations in health care practice 148
3.2.2 Probability of a case assertion (mind state) 152
3.2.3 Basic probability rules 155
3.2.4 Probability interpretations in object language and metalanguage 157
3.2.5 Body of evidence and medical interventions 161
3.3 Probabilities of Medical Conditionals 164
3.3.1 Standard logical relations and inference rules 164
3.3.2 Choosing a conditional probability form 166
3.3.3 Stochastic truth tables: A second look 176
3.3.4 More on probability calculation: Is there a probameter? 181
3.4 Stochastic Medical Inferences 186
3.4.1 From standard to stochastic syllogisms 187
3.4.2 Premise strengthening, internally consistent and uninformative inferences 199
3.5 Probability, Uncertainty and Information of Diagnoses or Prognoses Sets 205
3.6 Diagnosis Ranking and Symptom Confirmation Strength 211
3.6.1 Quantitative case parameters 212
3.6.2 Principles of medical practice and their quantitative expressions 215
3.7 The Trouble with Medical Probability 217
3.8 Translating Medical Assertions into Probabilistic Terms 222
3.9 Space-Time Reasoning Dynamics 229
3.9.1 Changes in assertions and substantive conditionals 229
3.9.2 Probability dynamics and hypothesis confirmation 235
3.9.3 The case of non-monotonic medical reasoning 238
3.10 Medical Syllogisms Involving Likelihood Ratios 240
3.11 Summing Up: Checking the Validity of Medical Arguments 242
3.12 Self-Referential Medical Assertions and Cognitive Favorability 244
3.13 Not Just a Set of Guidelines 247
Chapter 4 Space-Time Medical Mapping and Causation Modeling 249
4.1 Techniques With a "Health Warning" 249
4.2 Space-Time Disease Mapping 250
4.2.1 Objectives of medical mapping 251
4.2.2 The fundamental mapping equations 253
4.2.3 The insight behind the BME-SIR equations 256
4.2.4 A study of French flu 258
4.3 Modeling Space-Time Infectious Disease Spread 264
4.4 Space-Time Causation Revisited 268
4.5 Medical Causation in the SMR Inference Setting 271
4.5.1 Defining the problem 272
4.5.2 The role of KB and the interpretation of probabilistic causation 277
4.5.3 Causation: Epistemic vs. non-epistemic 280
4.5.4 Some remarks regarding the form of the causation conditional 283
4.5.5 Stochastic causal inferences 285
4.5.0 The role of secondary case attributes 287
4.6 Causation in Terms of Integrative Space-Time Prediction 289
4.7 Causation Justification and the Dualistic Opposition 291
Chapter 5 Looking Ahead 293
5.1 An Ibsenian Transformation 293
5.2 SMR and Divergence of Rationality in Medical Thinking 296
5.3 Challenges Emerging from the Incompleteness Principle and Unanticipated Knowledge 298
5.4 Information Technology-Based Medical Reasoning 302
5.5 Social and Cultural Dimensions of Medical Thinking 304
5.6 Quod Iacct Ante? 308
Bibliography 315
Index 331
