Support vector machine-based differentiation between aggressive and chronic periodontitis using microbial profiles.

Journal: International dental journal

PMID: 28771699

Abstract

BACKGROUND: The existence of specific microbial profiles for different periodontal conditions is still a matter of debate. The aim of this study was to test the hypothesis that 40 bacterial species could be used to classify patients, utilising machine learning, into generalised chronic periodontitis (ChP), generalised aggressive periodontitis (AgP) and periodontal health (PH).

Authors

Magda Feres

Department of Periodontology, Guarulhos University, Guarulhos, SP, Brazil.
Yoram Louzoun

Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel.
Simi Haber

Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel.
Marcelo Faveri

Department of Periodontology, Guarulhos University, Guarulhos, SP, Brazil.
Luciene C Figueiredo

Department of Periodontology, Guarulhos University, Guarulhos, SP, Brazil.
Liran Levin

Division of Periodontology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.

Keywords

Adult Aggressive Periodontitis Bacterial Load Biofilms Chronic Periodontitis Female Gingiva Humans Male Middle Aged Principal Component Analysis Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (28771699)

Support vector machine-based differentiation between aggressive and chronic periodontitis using microbial profiles.

Abstract

Authors

Keywords

External Resources

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