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<translate>Unfortunately, the two types of probability, the subjective probability and the objective one, are not accurately differentiated in medicine, and the same happens in other disciplines too. The fundamental fact remains that the most important meaning that probability theory has generated in medicine, particularly in the concepts of probability in aetiology, epidemiology, diagnostics and therapy, is its contribution to our understanding and representation of biological casuality.</translate>

<translate>Unfortunately, the two types of probability, the subjective probability and the objective one, are not accurately differentiated in medicine, and the same happens in other disciplines too. The fundamental fact remains that the most important meaning that probability theory has generated in medicine, particularly in the concepts of probability in aetiology, epidemiology, diagnostics and therapy, is its contribution to our understanding and representation of biological casuality.</translate>

==Probabilistic-causal analysis==

==<translate>Probabilistic-causal analysis</translate>==

From these premises it is clear that the clinical diagnosis is made using the so-called hypothetical-deductive method referred to as DN<ref name=":1">{{Cite book  

<translate>From these premises it is clear that the clinical diagnosis is made using the so-called hypothetical-deductive method referred to as DN</translate><ref name=":1">{{Cite book  

  | autore = Sarkar S

  | autore = Sarkar S

  | titolo = Nagel on Reduction

  | titolo = Nagel on Reduction

  | LCCN =  

  | LCCN =  

  | OCLC =  

  | OCLC =  

  }}</ref> ([https://en.wikipedia.org/wiki/Deductive-nomological_model deductive-nomological model]<ref>''DN model of scientific explanation'', also known as ''Hempel's model'', the ''Hempel–Oppenheim model'', the ''Popper–Hempel model'', or the ''covering law model''</ref>). But this is not realistic, since the medical knowledge used in clinical decision-making hardly contains causal deterministic laws to allow causal explanations and, hence, to formulate clinical diagnoses, among other things in the specialist context. Let us try to analyse again the case of our Mary Poppins, this time trying a probabilistic-causal approach.

  }}</ref> ([https://en.wikipedia.org/wiki/Deductive-nomological_model deductive-nomological model]<ref>''<translate>DN model of scientific explanation</translate>'', <translate>also known as</translate> ''<translate>Hempel's model</translate>'', ''Hempel–Oppenheim model'', ''Popper–Hempel model'', <translate>or</translate> ''<translate>covering law model</translate>''</ref>). <translate>But this is not realistic, since the medical knowledge used in clinical decision-making hardly contains causal deterministic laws to allow causal explanations and, hence, to formulate clinical diagnoses, among other things in the specialist context. Let us try to analyse again the case of our Mary Poppins, this time trying a probabilistic-causal approach.</translate>

Let us consider a number <math>n</math> of individuals including people who report Orofacial Pain who generally have bone degeneration of the Temporomandibular Joint. However, there may also be other apparently unrelated causes. We must mathematically translate the 'relevance' that these causal uncertainties have in determining a diagnosis.

<translate>Let us consider a number <math>n</math> of individuals including people who report Orofacial Pain who generally have bone degeneration of the Temporomandibular Joint. However, there may also be other apparently unrelated causes. We must mathematically translate the 'relevance' that these causal uncertainties have in determining a diagnosis.</translate>

===The casual relevance===

===The casual relevance===