Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

At least three phenotypes exist among periodontitis patients.

Journal of clinical periodontology - 1 Nov 2017

Delatola Chryssa, Loos Bruno G, Levin Evgeni, Laine Marja L

Abstract excerpt

AIM: To identify phenotypes of periodontitis patients by the use of an unsupervised modelling technique (clustering), based on pre-treatment radiographic and microbiological characteristics. MATERIALS AND METHODS: This retrospective study included data from 392 untreated periodontitis patients. Co-regularized spectral clustering algorithm was used to cluster the patients. The resulting clusters were subsequently...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Adolescent
Share to Age Factors
Share to Aggregatibacter actinomycetemcomitans

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Algorithms

Share to Alveolar Bone Loss

Share to Cluster Analysis

Share to Periodontitis

Share to Young Adult

Source

Identifiers

PMID: 28800144
DOI: 10.1111/jcpe.12797

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

At least three phenotypes exist among periodontitis patients.PMID 28800144Read ↗

Three periodontitis phenotypes: Bone loss patterns, antibiotic-surgical treatment and the new classification.Semantic proximity Read ↗

Unsupervised phenotyping of the periodontal architecture through high-dimensional clustering of electronic health records: A multicenter study.Semantic proximity Read ↗

Derivation and Validation of the Periodontal and Tooth Profile Classification System for Patient Stratification.Semantic proximity Read ↗

In search of appropriate measures of periodontal status: The Periodontal Profile Phenotype (P3 ) system.Semantic proximity Read ↗

Identifying predictors of the tooth loss phenotype in a large periodontitis patient cohort using a machine learning approach.Semantic proximity Read ↗

A novel classification of periodontal phenotype integrating hard and soft tissue parameters using data-driven clustering.Semantic proximity Read ↗

Gingival tissue transcriptomes identify distinct periodontitis phenotypes.Semantic proximity Read ↗

Modeling susceptibility to periodontitis.Semantic proximity Read ↗

Classification and diagnosis of aggressive periodontitisSemantic proximity Read ↗

Classification and diagnosis of aggressive periodontitisSemantic proximity Read ↗

RETRACTED: Comparison of Gingival Phenotype Classification Methods and Phenotype-Related Clinical ParametersSemantic proximity Read ↗

Molecular Signature of Peri-Implantitis: An AI-Driven Transcriptomic Analysis Reveals a Foreign-Body Inflammatory Phenotype; A Pilot StudySemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.