Suitability of machine learning models for prediction of clinically defined Stage III/IV periodontitis from questionnaires and demographic data in Danish cohorts.

Abstract

Authors

• C Enevold
  Institute for Inflammation Research, Center for Rheumatology and Spine Diseases, Copenhagen University Hospital, Copenhagen, Denmark.
• C H Nielsen
  Institute for Inflammation Research, Center for Rheumatology and Spine Diseases, Copenhagen University Hospital, Copenhagen, Denmark.
• L B Christensen
  Research Area Periodontology, Section for Oral Biology and Immunopathology, Department of Odontology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
• J Kongstad
  Research Area Periodontology, Section for Oral Biology and Immunopathology, Department of Odontology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
• N E Fiehn
  Costerton Biofilm Centre, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark.
• P R Hansen
  Department of Cardiology, Herlev-Gentofte Hospital, Hellerup, Denmark.
• P Holmstrup
  Research Area Periodontology, Section for Oral Biology and Immunopathology, Department of Odontology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
• A Havemose-Poulsen
  Research Area Periodontology, Section for Oral Biology and Immunopathology, Department of Odontology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
• C Damgaard
  Research Area Periodontology, Section for Oral Biology and Immunopathology, Department of Odontology, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.

Keywords

External Resources