Predictive modeling for peri-implantitis by using machine learning techniques

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 1408 impla...

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Detalles Bibliográficos
Autores principales: Mameno, Tomoaki, Wada, Masahiro, Nozaki, Kazunori, Takahashi, Toshihito, Tsujioka, Yoshitaka, Akema, Suzuna, Hasegawa, Daisuke, Ikebe, Kazunori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8160334/
https://www.ncbi.nlm.nih.gov/pubmed/34045590
http://dx.doi.org/10.1038/s41598-021-90642-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8160334/
https://www.ncbi.nlm.nih.gov/pubmed/34045590
http://dx.doi.org/10.1038/s41598-021-90642-4

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