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System logic Abstract

Versione del 30 dic 2025 alle 09:11 di Gianni (discussione | contributi) (Creata pagina con "{{main menu}} {{ArtBy| | autore = Gianni Frisardi | autore2 = Giorgio Cruccu | autore3 = Alice Bisirri | autore4 = Pier Paolo Valentini | autore5 = Flavio Frisardi | autore7 = Irene Minciacchi }} <div class="chapter-content"> '''Abstract:''' System Logic marks a shift in medical science when diagnosis must address living systems that are dynamic, layered, and only partially observable. This chapter explains why dentistry is being pushed toward System Logic by two conv...")
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System logic Abstract

Masticationpedia
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Abstract: System Logic marks a shift in medical science when diagnosis must address living systems that are dynamic, layered, and only partially observable. This chapter explains why dentistry is being pushed toward System Logic by two converging pressures: the demand for objective clinical indices and the recognition that the logic of medical language is often inadequate for complex biological phenomena. Indices and constants, such as the Henderson–Hasselbalch equation for pH or laboratory-derived composite markers, provide measurable reference points for diagnosis and guidelines. Yet their validity is frequently debated because clinical reality is not exhausted by what a single index measures, and because interpretation, schools of thought, and hidden variables can distort what looks like “objective” data.

Orthodontics provides a concrete illustration. Outcome assessment traditionally relied on clinician experience and subjective judgment, then moved toward standardized indices such as the Peer Assessment Rating (PAR) and objective grading systems for casts and radiographs. These tools quantify deviation from alignment, compare pre- and post-treatment states, and support quality improvement. However, an index may be accurate for alignment without being sufficient to define “normocclusion”, which is a functional and systemic condition. Relapse can occur even with apparently good occlusal finishing, and long-term changes can undermine cutoff-based excellence, reminding clinicians that indices are models, not reality.

This tension connects directly to language logic. Classical logic forces bivalent conclusions (true/false), while probabilistic reasoning often becomes meaningful only inside narrow specialist contexts; both can oversimplify signals that are context-dependent, driven by feedback, and sometimes non-deterministic. The chapter therefore extends the previous motivation for fuzzy logic: instead of separating specialist know-how, System Logic encourages the superimposition of interdisciplinary contexts, so that complex clinical phenomena can be described with elastic but formal rules.

Systems Theory is presented as the formal backbone for System Logic. A system is modeled through inputs, states, and outputs across ordered time. In the masticatory domain, the trigeminal motor system is treated as a black box: controlled triggers (transcranial electrical stimulation) act as inputs, and measurable responses (latency and amplitude) define outputs. The chapter contrasts routine interferential EMG, whose reliability and diagnostic correlation with TMD, orofacial pain, and malocclusion remain contested, with evoked-potential methods that embody system behavior and expose higher-level dysfunction.

Clinically, this approach aims to reduce differential diagnostic error, avoid unnecessary dental interventions in patients whose orofacial symptoms arise from neurological disease, and enable earlier, life-saving detection by grounding indices in system behavior and repeatable measurements. A worked example is the Root-MEP protocol: a sequence of progressively greater stimuli delivered at ordered times produces multiple averaged traces in which latency decreases and amplitude increases as input rises. Because the response is evoked at the trigeminal motor root level, it captures system integrity at a higher hierarchical level than the occlusal observable. Repeating the protocol across epochs allows comparison of the same system over time, turning a qualitative clinical impression into reproducible variables, and preparing the reader for later chapters on diagnostic modeling in practice.

Bilateral Root-MEPs
Figure: Virtual segmentation of the Trigeminal Nervous System and annotation of the motor Root level from which the trigeminal Motor Evoked Potentials (Root-MEPs) are evoked.

Three questions (Open Access)

«Why are clinical indices necessary but insufficient in dentistry?»
(They provide measurable reference points, but they can miss hidden variables and functional system states; an index may quantify alignment without defining normocclusion or safety.)
«What does “System Logic” add to medical language?»
(It moves beyond rigid true/false and narrow probabilistic framing by integrating elastic formal reasoning (including fuzzy concepts) with interdisciplinary context and feedback.)
«Why are Root-MEPs an example of Systems Theory applied clinically?»
(They treat the trigeminal motor system as a black box: a controlled input (trigger) produces measurable outputs (latency, amplitude) that track system integrity and can be compared across time.)

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