TY  - JOUR
ID  - eprints2377
TI  - Complex networks for data-driven medicine: the case of Class III dentoskeletal disharmony
AV  - public
JF  - New Journal of Physics
N2  - 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.
KW  - PACS: 87.19.L- Neuroscience; 87.80.-y Biophysical techniques (research methods); 87.59.B- Radiography;  87.10.-e General theory and mathematical aspects

UR  - http://dx.doi.org/10.1088/1367-2630/16/11/115017
IS  - 11
SN  - 1367-2630
PB  - IOPscience
VL  - 16
A1  - Scala, Antonio
A1  - Auconi, Pietro
A1  - Scazzocchio, Marco
A1  - Caldarelli, Guido
A1  - McNamara, James A.
A1  - Franchi, Lorenzo
Y1  - 2014/11//
ER  -