Predicting temporomandibular disorders in adults using interpretable machine learning methods: a model development and validation study

Predicting temporomandibular disorders in adults using interpretable machine learning methods: a model development and validation study

IntroductionTemporomandibular disorders (TMD) have a high prevalence and complex etiology. The purpose of this study was to apply a machine learning (ML) approach to identify risk factors for the occurrence of TMD in adults and to develop and validate an interpretable predictive model for the risk o...

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Bibliographic Details
Main Authors: Yuchen Cui, Fujia Kang, Xinpeng Li, Xinning Shi, Han Zhang, Xianchun Zhu
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-11-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
temporomandibular disorders
machine learning
prediction model
shapley additive explanations
random forest
Online Access:https://www.frontiersin.org/articles/10.3389/fbioe.2024.1459903/full
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