A network approach to orthodontic diagnosis (Articolo in rivista)

Type
Label
  • A network approach to orthodontic diagnosis (Articolo in rivista) (literal)
Anno
  • 2011-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1111/j.1601-6343.2011.01523.x (literal)
Alternative label
  • P. Auconi (1); G. Caldarelli (1,2,4); A. Scala (1,2); G. Ierardo (3); A. Polimeni (3) (2011)
    A network approach to orthodontic diagnosis
    in Orthodontics & craniofacial research (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • P. Auconi (1); G. Caldarelli (1,2,4); A. Scala (1,2); G. Ierardo (3); A. Polimeni (3) (literal)
Pagina inizio
  • 189 (literal)
Pagina fine
  • 197 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 14 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 4 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1) CNR Centre for Statistical Mechanics and Complexity, Physics Department, 'Sapienza' University of Rome, Rome, Italy 2) London Institute of Mathematical Sciences, Mayfair, London, UK 3) Department of Pediatric Dentistry, 'Sapienza' University of Rome, Rome, Italy 4) Centro Sistemi Complessi CNR, Dipartimento di Fisica Sapienza Universita' di Roma Piazzale Aldo Moro 5 Roma 00185, Italy (literal)
Titolo
  • A network approach to orthodontic diagnosis (literal)
Abstract
  • Background - Network analysis, a recent advancement in complexity science, enables understanding of the properties of complex biological processes characterized by the interaction, adaptive regulation, and coordination of a large number of participating components. Objective - We applied network analysis to orthodontics to detect and visualize the most interconnected clinical, radiographic, and functional data pertaining to the orofacial system. Materials and Methods - The sample consisted of 104 individuals from 7 to 13 years of age in the mixed dentition phase without previous orthodontic intervention. The subjects were divided according to skeletal class; their clinical, radiographic, and functional features were represented as vertices (nodes) and links (edges) connecting them. Results - Class II subjects exhibited few highly connected orthodontic features (hubs), while Class III patients showed a more compact network structure characterized by strong co-occurrence of normal and abnormal clinical, functional, and radiological features. Restricting our analysis to the highest correlations, we identified critical peculiarities of Class II and Class III malocclusions. Conclusions - The topology of the dentofacial system obtained by network analysis could allow orthodontists to visually evaluate and anticipate the co-occurrence of auxological anomalies during individual craniofacial growth and possibly localize reactive sites for a therapeutic approach to malocclusion. (literal)
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