Bayesian networks analysis of malocclusion data

A simplifed DAG

Scientific Reports 7, 1 (2017)

M. Scutari, P. Auconi, G. Caldarelli, L. Franchi

LQ placeholder A simplifed DAG

In this paper we use Bayesian networks to determine and visualise the interactions among various Class III malocclusion maxillofacial features during growth and treatment. We start from a sample of 143 patients characterised through a series of a maximum of 21 different craniofacial features. We estimate a network model from these data and we test its consistency by verifying some commonly accepted hypotheses on the evolution of these disharmonies by means of Bayesian statistics. We show that untreated subjects develop different Class III craniofacial growth patterns as compared to patients submitted to orthodontic treatment with rapid maxillary expansion and facemask therapy. Among treated patients the CoA segment (the maxillary length) and the ANB angle (the antero-posterior relation of the maxilla to the mandible) seem to be the skeletal subspaces that receive the main effect of the treatment.

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Network valuation in financial systems

P. Barucca, M. Bardoscia, F. Caccioli, M. D’Errico, G. Visentin, G. Caldarelli, S. Battiston

Mathematical Finance

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The space of functions computed by deep layered machines

A. Mozeika, B. Li, D. Saad

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T. Coolen, M. Sheikh, A. Mozeika, F. Aguirre-Lopez, F. Antenucci

Sub. to Journal of Physics A

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Taming complexity

M. Reeves, S. Levin, T. Fink, A. Levina

Harvard Business Review

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Replica analysis of Bayesian data clustering

A. Mozeika, T. Coolen

Journal of Physics A

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F. Vanni, P. Barucca

Journal of Economic Interaction and Coordination

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