Predictive modeling for peri-implantitis by using machine learning techniques

Abstract The purpose of this retrospective cohort study was to create a model for predicting the onset of peri-implantitis by using machine learning methods and to clarify interactions between risk indicators. This study evaluated 254 implants, 127 with and 127 without peri-implantitis, from among 1...

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Auteurs principaux: Tomoaki Mameno, Masahiro Wada, Kazunori Nozaki, Toshihito Takahashi, Yoshitaka Tsujioka, Suzuna Akema, Daisuke Hasegawa, Kazunori Ikebe
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/d9b9b3695a65420184b374821fe3a48f
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