This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3299) Clinical Information and Decision Making (1956) Artificial Intelligence (2194) Dental Sciences (172) Decision Support for Health Professionals (1564) Machine Learning (2125)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48351, first published .
Development of Risk Prediction Models for Severe Periodontitis in a Thai Population: Statistical and Machine Learning Approaches

Development of Risk Prediction Models for Severe Periodontitis in a Thai Population: Statistical and Machine Learning Approaches

Development of Risk Prediction Models for Severe Periodontitis in a Thai Population: Statistical and Machine Learning Approaches

Authors of this article:

Htun Teza1 Author Orcid Image ;   Anuchate Pattanateepapon1 Author Orcid Image ;   Attawood Lertpimonchai2, 3 Author Orcid Image ;   Prin Vathesatogkit4 Author Orcid Image ;   Gareth J McKay5 Author Orcid Image ;   John Attia6 Author Orcid Image ;   Ammarin Thakkinstian1 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Dhungana G, Srisai D, Sampath C, Soliman J, Kelly R, Saleh H, Sedik A, Raynes E, Ferguson A, Alluri L, Gangula P. Unveiling the Molecular Crosstalk Between Periodontal and Cardiovascular Diseases: A Systematic Review. Dentistry Journal 2025;13(3):98 View
  2. Montero E, Sánchez N, Sanz‐Sánchez I, López‐Durán M, de Albornoz A, Dietrich T. Emerging Technologies and Algorithms for Periodontal Screening and Risk of Disease Progression in Non‐Dental Settings: A Scoping Review. Journal of Clinical Periodontology 2025;52(S29):246 View
  3. Wu L, Su S, Salama E, Ma X, Chen L, Wang Y. Predicting plaque-gingivitis risk in schoolchildren using an interpretable machine learning model: a cross-sectional study. BMC Oral Health 2025;25(1) View