The Validity of Machine Learning Procedures in Orthodontics: What Is Still Missing?

Journal of Personalized Medicine

Antonella Polimeni¹  Matteo Saccucci¹  Gabriele Di Carlo¹  Guido Caldarelli²  Silvia Capuani²  Tommaso Gili³  Pietro Auconi⁴ 

[1] Department of Oral and Maxillo-Facial Sciences, Sapienza University of Rome, Viale Regina Elena 287a, 00161 Rome, Italy;ISC CNR, Department of Physics, University of Rome “Sapienza”, P.le Aldo Moro 5, 00185 Rome, Italy;Networks Unit, IMT School for Advanced Studies Lucca, Piazza San Francesco 19, 55100 Lucca, Italy;Private Practice of Orthodontics, 00012 Rome, Italy;

关键词: machine learning;    artificial intelligence;    orthodontics;    complexity;    prognosis optimization;   

DOI  :  10.3390/jpm12060957

来源: DOAJ

【 摘 要 】

Artificial intelligence (AI) models and procedures hold remarkable predictive efficiency in the medical domain through their ability to discover hidden, non-obvious clinical patterns in data. However, due to the sparsity, noise, and time-dependency of medical data, AI procedures are raising unprecedented issues related to the mismatch between doctors’ mentalreasoning and the statistical answers provided by algorithms. Electronic systems can reproduce or even amplify noise hidden in the data, especially when the diagnosis of the subjects in the training data set is inaccurate or incomplete. In this paper we describe the conditions that need to be met for AI instruments to be truly useful in the orthodontic domain. We report some examples of computational procedures that are capable of extracting orthodontic knowledge through ever deeper patient representation. To have confidence in these procedures, orthodontic practitioners should recognize the benefits, shortcomings, and unintended consequences of AI models, as algorithms that learn from human decisions likewise learn mistakes and biases.

【 授权许可】

Unknown