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Article

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

Journal of periodontology - 1 Aug 2026

Chatzopoulos Georgios S, Wolff Larry F

Abstract excerpt

BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characterizing disease patterns based on the "periodontal architecture" of localized structural failures (tooth mobility and molar furcation defects) rather than global severity averages alone. METHODS: This cross-sectional study analyzed electronic health records from 15,723...

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Identifiers

PMID: 41973035
DOI: 10.1002/jper.70123
PMCID: PMC13502441

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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