E-raamat: Causality, Probability, and Medicine

(University College London, UK)
  • Formaat: 300 pages, 2 Tables, black and white
  • Ilmumisaeg: 15-Aug-2018
  • Kirjastus: Routledge
  • ISBN-13: 9781317564294
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  • Formaat: 300 pages, 2 Tables, black and white
  • Ilmumisaeg: 15-Aug-2018
  • Kirjastus: Routledge
  • ISBN-13: 9781317564294

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Why is understanding causation so important in philosophy and the social sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine little attempt has been made to connect causation and probability with medicine itself. Causality, Probability and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories of causality in philosophy, including action-related theories, causality and mechanisms and causality and probability. Throughout the book he applies them to important discoveries and theories within medicine, such as germ theory; tuberculosis and cholera; smoking and heart disease; the first ever RCT designed to test the treatment of tuberculosis; the growing area of philosophy of evidence-based medicine; and philosophy of epidemiology.This book will be of great interest to students and researchers in philosophy of science and philosophy of medicine, as well as those working in medicine, nursing and related health disciplines where a working knowledge of causality and probability is required.

Arvustused

"This book is just what philosophy of medicine needs - careful argumentative analysis of issues that matter to the practice of biomedical science." - Harold Kincaid, University of Cape Town, South Africa "With his usual clarity, Professor Gillies manages to deal simultaneously with two among the most complex and thorny issues in science and philosophy of science: causality and probability. And he does so in a field - medicine - where their complexity grows exponentially, because of the theoretical and practical challenges of understanding and curing disease. The book is therefore an essential guide to those who want to delve into medicine." - Federica Russo, University of Amsterdam, The Netherlands "This book develops a philosophical theory of causality in a very engaging and readable way. It sheds light on many historical examples of medical discovery and also on present-day causal modelling methods. Essential reading for anyone interested in causality, probability, or medicine." - Jon Williamson, University of Kent, UK

Acknowledgements xii
Preface xv
Introduction
1(14)
0.1 Deterministic and indeterministic causality
2(2)
0.2 AIM (Action, Intervention, Manipulation) theories of causality
4(1)
0.3 Mechanistic theories of causality
5(3)
0.4 Probabilistic theories of causality
8(5)
Notes
13(2)
Part I Causality and action 15(54)
1 An action-related theory of causality
17(13)
1.1 Russell's critique of the notion of cause
19(2)
1.2 Collingwood's AIM theory of causality
21(3)
1.3 Productive actions and avoidance actions
24(5)
Notes
29(1)
2 General discussion of AIM theories of causality
30(15)
2.1 Gasking's contribution
30(1)
2.2 Objection
1. Some causes cannot be manipulated
31(6)
2.3 Objection
2. Causes exist independently of humans
37(1)
2.4 Objection
3. Unavoidable circularity
38(2)
2.5 Explanation of causal asymmetry
40(5)
3 An example from medicine: Koch's work on bacterial diseases and his postulates
45(24)
3.1 The background to Koch's work
45(2)
3.2 Koch's investigations of tuberculosis and cholera
47(3)
3.3 Koch's postulates
50(5)
3.4 Modification of the postulates in the light of the action-related theory of causality
55(2)
3.5 Koch establishes that the comma bacillus is the cause of cholera
57(10)
Notes
67(2)
Part II Causality and mechanisms 69(124)
4 Mechanistic theories of causality and causal theories of mechanism
71(19)
4.1 The Dowe-Salmon theory of causality
71(1)
4.2 Criticism of the Dowe-Salmon theory of causality
72(1)
4.3 More general definitions of mechanism
73(6)
4.4 A causal theory of mechanisms in medicine
79(2)
4.5 The usefulness of postulating mechanisms for the confirmation of causal hypotheses and for discovering cures
81(1)
4.6 Causes, activities, and Anscombe
82(7)
Note
89(1)
5 Types of evidence: (i) Evidence of mechanism
90(12)
5.1 Confirmation and disconfirmation of causal hypotheses in medicine
90(1)
5.2 Two kinds of evidence
91(1)
5.3 Coronary heart disease (CHD)
92(3)
5.4 An example of evidence of mechanism: Anitschkow's study of experimental atherosclerosis in rabbits
95(6)
Notes
101(1)
6 Types of evidence: (ii) Statistical evidence in human populations
102(26)
6.1 Ancel Keys and the dangers of saturated fat
102(6)
6.2 An example of observational statistical evidence: The seven countries study
108(7)
6.3 The problem of confounders, and the disconfirmation of causal hypotheses
115(3)
6.4 Some further general points regarding the seven countries study
118(1)
6.5 Examples of interventional statistical evidence: Some clinical trials
119(8)
Note
127(1)
7 Combining statistical evidence with evidence of mechanism
128(5)
7.1 Combining the results of Anitschkow, Dayton et al., and Keys et al.
128(1)
7.2 Strength through combining
129(3)
Note
132(1)
8 The Russo-Williamson thesis: (i) Effects of smoking on health
133(17)
8.1 Statement of the Russo-Williamson thesis
133(1)
8.2 Some different views concerning the roles of statistical evidence and evidence of mechanism in medicine
134(2)
8.3 Smoking and lung cancer
136(5)
8.4 Smoking and heart disease: Is there a linking mechanism?
141(2)
8.5 Research into atherosclerosis 1979-89
143(2)
8.6 Research into atherosclerosis in the 1990s
145(3)
8.7 Implications of our medical examples for the Russo-Williamson thesis
148(1)
Note
149(1)
9 The Russo-Williamson thesis: (ii) The evaluation of streptomycin and thalidomide
150(13)
9.1 Evidence-based medicine
150(3)
9.2 The trial of streptomycin against bed-rest
153(2)
9.3 The investigation of the treatment mechanism
155(1)
9.4 The trials of streptomycin and PAS
156(2)
9.5 The streptomycin trials in relation to EBM and RWT
158(1)
9.6 Generalizing from the streptomycin case, and the example of thalidomide
158(4)
Notes
162(1)
10 Objections to the Russo-Williamson thesis
163(22)
10.1 Causal pluralism
163(1)
10.2 McArdle disease
164(4)
10.3 The Semmelweis case
168(6)
10.4 Alternative medicine
174(3)
10.5 Other statistical counter-examples
177(8)
11 Discovering cures in medicine and seeking for deeper explanations
185(8)
11.1 The importance of mechanisms for discovering cures in medicine
185(3)
11.2 Seeking deeper explanations in medicine and physics
188(5)
Part III Causality and probability 193(66)
12 Indeterministic causality
195(9)
12.1 The causation of cervical cancer
197(3)
12.2 Probabilistic causality
200(3)
Note
203(1)
13 Causal networks
204(21)
13.1 Conjunctive and interactive forks
204(4)
13.2 Multi-causal forks
208(3)
13.3 The rise of fast food, and the failure of the 'Eat Well and Stay Well' project
211(11)
13.4 The Hesslow counter-example revisited
222(1)
Notes
223(2)
14 How should probabilities be interpreted?
225(11)
14.1 Interpretations of probability
226(3)
14.2 Interpreting the probabilities in causal models
229(3)
14.3 Simpson's paradox
232(1)
14.4 Comparison with other suggested solutions
233(2)
Notes
235(1)
15 Pearl's alternative approach to linking causality and probability
236(16)
15.1 Debates about the Markov condition
236(7)
15.2 Pearl's alternative approach
243(3)
15.3 Restoring the Markov condition by adjusting the model
246(5)
Notes
251(1)
16 Extension of the action-related theory to the indeterministic case
252(7)
16.1 Mathematical formulation of the problem
252(2)
16.2 Informal statement of Sudbury's theorems
254(2)
16.3 Extension of the action-related theory to the indeterministic case
256(1)
Notes
257(2)
Appendix 1: Example of a simple medical intervention which is not an intervention in Woodward's sense 259(3)
Appendix 2: Mathematical terminology 262(2)
Appendix 3: Sudbury's theorems 264(4)
Glossary of medical terms 268(15)
References 283(11)
Index 294
Donald Gillies is Emeritus Professor of Philosophy of Science and Mathematics at University College London, UK.