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Estimating Periodontitis Susceptibility Cases for Epidemiological Studies with Multiple Imputation.
Zhang, L; Xiao, M; Chu, H; Kotsakis, G A; Guan, W.
Afiliação
  • Zhang L; Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
  • Xiao M; Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Chu H; Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
  • Kotsakis GA; Statistical Research and Data Science Center, Pfizer Inc., New York, NY, USA.
  • Guan W; Department of Oral Biology & Clinical Research Center, Rutgers School of Dental Medicine, Newark, NJ, USA.
JDR Clin Trans Res ; 9(4): 378-386, 2024 Oct.
Article em En | MEDLINE | ID: mdl-38482579
ABSTRACT
KNOWLEDGE TRANSFER STATEMENT Our proposed estimate of periodontitis susceptibility cases addresses the issue of missing teeth, offering an innovative solution through a generative missing data imputation model. The implications of our findings extend to fostering more robust investigations into the relationships between periodontal health and systemic diseases, thereby offering valuable insights to clinicians for informed decision-making. Moreover, the study's capacity to shape clinical practices and interventions in public health will further fortify health policy strategies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Periodontite Limite: Humans Idioma: En Revista: JDR Clin Trans Res Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Periodontite Limite: Humans Idioma: En Revista: JDR Clin Trans Res Ano de publicação: 2024 Tipo de documento: Article