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<translate>We will remarkably notice the following deductions</translate>: | <translate>We will remarkably notice the following deductions</translate>: | ||
*'''Classical Logic''' in the Dental Context <math>{A}</math> in which only a logical process that gives as results <math>\mu_{\displaystyle {{A}}}(x)= 1 </math> | *'''<translate>Classical Logic</translate>''' <translate>in the Dental Context</translate> <math>{A}</math> <translate>in which only a logical process that gives as results</translate> <math>\mu_{\displaystyle {{A}}}(x)= 1 </math> <translate>will be possible, or</translate> <math>\mu_{\displaystyle {{A}}}(x)= 0 </math> <translate>being the range of data</translate> <math>D=\{\delta_1,\dots,\delta_4\}</math> <translate>reduced to basic knowledge</translate> <math>KB</math> <translate>in the set</translate> <math>{A}</math>. <translate>This means that outside the dental world there is a void and that term of set theory is written precisely</translate> <math>\mu_{\displaystyle {{A}}}(x)= 0 </math> <translate>and which is synonymous with a high range of</translate>: | ||
<br />{{q2|Differential diagnostic error|}} | <br />{{q2|<translate>Differential diagnostic error</translate>|}} | ||
*'''Fuzzy logic''' in a dental context <math>\tilde{A}</math> in which they are represented beyond the basic knowledge <math>KB</math> of the dental context also those partially acquired from the neurophysiological world <math>0<\mu_ {\tilde {A}}(x) < 1</math> will have the prerogative to return a result <math>\mu_\tilde{A}(x)= 1 | *'''<translate>Fuzzy logic</translate>''' <translate>in a dental context</translate> <math>\tilde{A}</math> <translate>in which they are represented beyond the basic knowledge</translate> <math>KB</math> <translate>of the dental context also those partially acquired from the neurophysiological world</translate> <math>0<\mu_ {\tilde {A}}(x) < 1</math> <translate>will have the prerogative to return a result</translate> <math>\mu_\tilde{A}(x)= 1 | ||
</math> and a result <math>0<\mu_ {\tilde {A}}(x) < 1</math> because of | </math> <translate>and a result</translate> <math>0<\mu_ {\tilde {A}}(x) < 1</math> <translate>because of basic knowledge</translate> <math>KB</math> <translate>which at this point is represented by the union of</translate> <math>KB_c</math> <translate>dental and neurological contexts</translate>. <translate>The result of this scientific-clinical implementation of dentistry would allow a</translate> {{q2|<translate>Reduction of differential diagnostic error</translate>|}} | ||
==Final considerations== | ==<translate>Final considerations</translate>== | ||
Topics that could distract the reader’s | <translate>Topics that could distract the reader’s attention were, in fact, essential for demonstrating the message</translate>. <translate>Normally, indeed, when any more or less brilliant mind allows itself to throw a stone into the pond of Science, a shockwave is generated, typical of the period of Kuhn’s extraordinary science, against which most of the members of the international scientific community row</translate>. <translate>With good faith, we can say that this phenomenon—as regards the topics we are addressing here—is well represented in the premise at the beginning of the chapter</translate>. | ||
In these chapters, | <translate>In these chapters, actually, a fundamental topic for science has been approached</translate>: <translate>the re-evaluation, the specific weight that has always been given to</translate> <math>P-value</math>, <translate>awareness of scientific / clinical contexts</translate> <math>KB_c</math>, <translate>having undertaken a more elastic path of Fuzzy Logic than the Classical one, realizing the extreme importance of</translate> <math>KB</math> <translate>and ultimately the union of contexts</translate> <math>KB_c</math> <translate>to increase its diagnostic capacity</translate>.<ref>Mehrdad Farzandipour, Ehsan Nabovati, Soheila Saeedi, Esmaeil Fakharian. [https://pubmed.ncbi.nlm.nih.gov/30119845/ Fuzzy decision support systems to diagnose musculoskeletal disorders: A systematic literature review] . Comput Methods Programs Biomed. 2018 Sep;163:101-109. doi: 10.1016/j.cmpb.2018.06.002. Epub 2018 Jun 6.</ref><ref>Long Huang, Shaohua Xu, Kun Liu, Ruiping Yang, Lu Wu. [https://pubmed.ncbi.nlm.nih.gov/34257635/ A Fuzzy Radial Basis Adaptive Inference Network and Its Application to Time-Varying Signal Classification] . Comput Intell Neurosci, 2021 Jun 23;2021:5528291.<br>doi: 10.1155/2021/5528291.eCollection 2021.</ref> | ||
<translate>In the next chapter we will be ready to undertake an equally fascinating path: it will leads us to the context of a System Language logic, and will allow us to deepen our knowledge, no longer in clinical semeiotics only, but in the understanding of system functions (recently it is being evaluated in neuromotor disciplines for Parkinson's disease)</translate>.<ref>Mehrbakhsh Nilashi, Othman Ibrahim, Ali Ahani. [https://pubmed.ncbi.nlm.nih.gov/27686748/ Accuracy Improvement for Predicting Parkinson's Disease Progression.] Sci Rep. 2016 Sep 30;6:34181. | |||
doi: 10.1038/srep34181.</ref> | |||
<translate>In Masticationpedia, of course, we will report the topic 'System Inference' in the field of the masticatory system as we could read in the next chapter entitled 'System logic'</translate>. | |||
{{Btnav|The logic of probabilistic language|Introduction}} | {{Btnav|The logic of probabilistic language|Introduction}} |
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