Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics. (14th September 2021)

• Record Type: Journal Article
• Authors: Gili, Tommaso; Di Carlo, Gabriele; Capuani, Silvia; Auconi, Pietro; Caldarelli, Guido; Polimeni, Antonella
• Other Names: Yamashiro Takashi guestEditor.; Ko Ching‐Chang guestEditor.
• Is Part Of: Orthodontics and craniofacial research. Volume 24(2021)Supplement 2
• Page Start: 16
• Page End: 25
• Publication Date: 2021-09-14
• Subjects: artificial intelligence -- big data -- complexity -- machine learning -- musculoskeletal magnetic resonance imaging -- network medicine -- orthodontics; Skull -- Growth -- Periodicals; Facial bones -- Growth -- Periodicals; Orthodontics -- Periodicals; Orthodontics, Corrective -- Periodicals; Orthodontic appliances -- Periodicals; 617.51
• DOI: 10.1111/ocr.12520
• Languages: English
• ISSNs: 1601-6335

Abstract

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.