The idea of classifying and defining bruxism according to ontological principles may be interesting, but currently we just do not have enough information to label in a black or white manner the many facets of bruxism. In an era in which general knowledge on bruxism by the dental communities is surely in need of improvement, efforts to clarify the road map tracked by the current panelists who drafted the definition should be appraised carefully. The recent introduction of a standardized multidimensional evaluation system (i.e., Standardized Tool for the Assessment of Bruxism [STAB]) and a screening instrument for bruxism (i.e., BruxScreen) should be viewed as the starting points to enter a new era in the discipline of bruxism, in which non-hierarchical and non-preconceived approaches are used to collect data. Artificial intelligence strategies to mine data gathered with the above instruments might help building predictive models along the etiology-status-consequences trajectory, as recently suggested in a model for awake bruxism metrics. Until then, proposals to adopt ontological principles to classify bruxism will be merely based on speculations rather than on facts.
Manfredini, D., Lobbezoo, F. (2024). Ontology and Bruxism: Do We Have Enough Information?. JOURNAL OF ORAL REHABILITATION [10.1111/joor.13890].
Ontology and Bruxism: Do We Have Enough Information?
Manfredini D.
;
2024-01-01
Abstract
The idea of classifying and defining bruxism according to ontological principles may be interesting, but currently we just do not have enough information to label in a black or white manner the many facets of bruxism. In an era in which general knowledge on bruxism by the dental communities is surely in need of improvement, efforts to clarify the road map tracked by the current panelists who drafted the definition should be appraised carefully. The recent introduction of a standardized multidimensional evaluation system (i.e., Standardized Tool for the Assessment of Bruxism [STAB]) and a screening instrument for bruxism (i.e., BruxScreen) should be viewed as the starting points to enter a new era in the discipline of bruxism, in which non-hierarchical and non-preconceived approaches are used to collect data. Artificial intelligence strategies to mine data gathered with the above instruments might help building predictive models along the etiology-status-consequences trajectory, as recently suggested in a model for awake bruxism metrics. Until then, proposals to adopt ontological principles to classify bruxism will be merely based on speculations rather than on facts.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/1279035