A personalized periodontitis risk based on nonimage electronic dental records by machine learning.

Journal: Journal of dentistry
PMID:

Abstract

OBJECTIVE: This study aimed to develop a machine-learning (ML) model to predict the risk for Periodontal Disease (PD) based on nonimage electronic dental records (EDRs).

Authors

  • Laura Swinckels
    Department of Oral Public Health, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit, Amsterdam, Netherlands.
  • Ander de Keijzer
    Data Driven Smart Society Research Group, Faculty of Engineering, Design & Computing, Inholland University of Applied Sciences, Alkmaar, Netherlands.
  • Bruno G Loos
    Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, The Netherlands.
  • Reuben Joseph Applegate
    Biomedical Informatics Group-Analytics Research Center, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Krishna Kumar Kookal
    Technology Services and Informatics, School of Dentistry, University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Elsbeth Kalenderian
    Marquette University School of Dentistry, Milwaukee, WI, USA; University of Pretoria School of Dentistry, Pretoria, South Africa.
  • Harmen Bijwaard
    Medical Technology Research Group, Cluster Health, Sport and Welfare, Inholland University of Applied Sciences, Haarlem, Netherlands.
  • Josef Bruers
    Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, The Netherlands; Royal Dutch Dental Association (KNMT), Utrecht, The Netherlands.