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Difference between revisions of "Fuzzy language logic"
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| autore3 = Flavio Frisardi | | autore3 = Flavio Frisardi | ||
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In this chapter, we delve into the cognitive limits of diagnostic reasoning, focusing on how knowledge in medical science is bound by time and context, represented by two parameters: <math>KB_t</math> (time-dependent knowledge base) and <math>KB_c</math> (context-dependent knowledge base). These parameters emphasize how scientific knowledge evolves and is shaped by the specific context in which it operates. Through practical examples, such as research on Temporomandibular Disorders (TMD) and Orofacial Pain (OP), we illustrate the interconnectedness of scientific fields and the significant drop in knowledge integration when topics are combined. | |||
The discussion moves from the limitations of classical logic to the broader framework of probabilistic reasoning, and eventually to fuzzy logic. We examine how classical logic, with its binary nature, is inadequate for medical diagnosis, where uncertainty is inherent. By introducing fuzzy logic, a multivalent approach, we show how it is better suited to handling the complexities and uncertainties of clinical cases, such as that of Mary Poppins. | |||
Fuzzy logic allows for a more flexible representation of truth, enabling the partial inclusion of concepts within sets, and thus reducing diagnostic errors. The chapter emphasizes the importance of expanding our knowledge base across different contexts and integrating interdisciplinary perspectives, particularly in dentistry and neurophysiology. Finally, it concludes with a call for continued exploration of system logic, setting the stage for the following chapter on the "System Language Logic." | |||
==Introduction== | ==Introduction== | ||
We have come this far because, as colleagues, are very often faced with responsibilities and decisions that are very difficult to take and issues such as conscience, intelligence and humility come into play. In such a situation, however, we are faced with two equally difficult obstacles to manage that of one <math>KB</math> (Knowledge Basis), as we discussed in the chapter ‘[[The logic of probabilistic language|Logic of probabilistic language]]’, limited in the time that we codify in <math>KB_t</math> and one <math>KB</math> limited in the specific context (<math>KB_c</math>). These two parameters of epistemology characterize the scientific age in which we live. Also, both <math>KB_t</math> that the <math>KB_c</math> are dependent variables of our phylogeny, and, in particular of our conceptual plasticity and attitude to change.<ref>{{Cite book | We have come this far because, as colleagues, are very often faced with responsibilities and decisions that are very difficult to take and issues such as conscience, intelligence and humility come into play. In such a situation, however, we are faced with two equally difficult obstacles to manage that of one <math>KB</math> (Knowledge Basis), as we discussed in the chapter ‘[[The logic of probabilistic language|Logic of probabilistic language]]’, limited in the time that we codify in <math>KB_t</math> and one <math>KB</math> limited in the specific context (<math>KB_c</math>). These two parameters of epistemology characterize the scientific age in which we live. Also, both <math>KB_t</math> that the <math>KB_c</math> are dependent variables of our phylogeny, and, in particular of our conceptual plasticity and attitude to change.<ref>{{Cite book | ||