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Bayesian networks analysis of malocclusion data

Abstract:

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...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41598-017-15293-w

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Publisher:
Nature Publishing Group Publisher's website
Journal:
Scientific Reports Journal website
Volume:
7
Pages:
15236
Publication date:
2017-11-01
Acceptance date:
2017-05-22
DOI:
EISSN:
2045-2322
ISSN:
2045-2322
Source identifiers:
696718
Keywords:
Subjects:
Pubs id:
pubs:696718
UUID:
uuid:8c571494-126b-424d-9953-654491a565f8
Local pid:
pubs:696718
Deposit date:
2017-05-23

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