eprintid: 2377
rev_number: 8
eprint_status: archive
userid: 6
dir: disk0/00/00/23/77
datestamp: 2014-12-01 10:28:46
lastmod: 2014-12-01 10:28:46
status_changed: 2014-12-01 10:28:46
type: article
metadata_visibility: show
creators_name: Scala, Antonio
creators_name: Auconi, Pietro
creators_name: Scazzocchio, Marco
creators_name: Caldarelli, Guido
creators_name: McNamara, James A.
creators_name: Franchi, Lorenzo
creators_id: 
creators_id: 
creators_id: 
creators_id: guido.caldarelli@imtlucca.it
creators_id: 
creators_id: 
title: Complex networks for data-driven medicine: the case of Class III dentoskeletal disharmony
ispublished: pub
subjects: QC
subjects: R1
divisions: EIC
full_text_status: public
keywords: PACS: 87.19.L- Neuroscience; 87.80.-y Biophysical techniques (research methods); 87.59.B- Radiography;  87.10.-e General theory and mathematical aspects

abstract: In the last decade, the availability of innovative algorithms derived from complexity theory has inspired the development of highly detailed models in various fields, including physics, biology, ecology, economy, and medicine. Due to the availability of novel and ever more sophisticated diagnostic procedures, all biomedical disciplines face the problem of using the increasing amount of information concerning each patient to improve diagnosis and prevention. In particular, in the discipline of orthodontics the current diagnostic approach based on clinical and radiographic data is problematic due to the complexity of craniofacial features and to the numerous interacting co-dependent skeletal and dentoalveolar components. In this study, we demonstrate the capability of computational methods such as network analysis and module detection to extract organizing principles in 70 patients with excessive mandibular skeletal protrusion with underbite, a condition known in orthodontics as Class III malocclusion. Our results could possibly constitute a template framework for organising the increasing amount of medical data available for patients' diagnosis.
date: 2014-11
date_type: published
publication: New Journal of Physics
volume: 16
number: 11
publisher: IOPscience
pagerange: 115017
id_number: doi:10.1088/1367-2630/16/11/115017
refereed: TRUE
issn: 1367-2630
official_url: http://dx.doi.org/10.1088/1367-2630/16/11/115017
citation:   Scala, Antonio and Auconi, Pietro and Scazzocchio, Marco and Caldarelli, Guido and McNamara, James A. and Franchi, Lorenzo  Complex networks for data-driven medicine: the case of Class III dentoskeletal disharmony.  New Journal of Physics, 16 (11).  p. 115017.  ISSN 1367-2630      (2014)  
document_url: http://eprints.imtlucca.it/2377/1/Caldarelli_IOP_2014.pdf