Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics.

Journal: Orthodontics & craniofacial research
Published Date:

Abstract

Procedures and models of computerized data analysis are becoming researchers' and practitioners' thinking partners by transforming the reasoning underlying biomedicine. Complexity theory, Network analysis and Artificial Intelligence are already approaching this discipline, intending to provide support for patient's diagnosis, prognosis and treatments. At the same time, due to the sparsity, noisiness and time-dependency of medical data, such procedures are raising many unprecedented problems related to the mismatch between the human mind's reasoning and the outputs of computational models. Thanks to these computational, non-anthropocentric models, a patient's clinical situation can be elucidated in the orthodontic discipline, and the growth outcome can be approximated. However, to have confidence in these procedures, orthodontists should be warned of the related benefits and risks. Here we want to present how these innovative approaches can derive better patients' characterization, also offering a different point of view about patient's classification, prognosis and treatment.

Authors

  • Tommaso Gili
    Networks Unit, IMT School for Advanced Studies Lucca, Lucca, Italy.
  • Gabriele Di Carlo
    Department of Oral and Maxillo-Facial Sciences, Sapienza University of Rome, Rome, Italy.
  • Silvia Capuani
    CNR-ISC Unità Sapienza, Rome, Italy.
  • Pietro Auconi
    Private Practice Rome, Rome, Italy.
  • Guido Caldarelli
    CNR-ISC Unità Sapienza, Rome, Italy.
  • Antonella Polimeni
    Department of Oral and Maxillo Facial Sciences, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy.