Developing Predictive Models for Periodontitis Progression Using Artificial Intelligence: A Longitudinal Cohort Study.

Journal: Journal of clinical periodontology
Published Date:

Abstract

AIM: To construct predictive models of periodontitis progression by applying Machine Learning (ML) to baseline data from a study of periodontitis progression.

Authors

  • Camila Pinheiro Furquim
    Department of Basic & Translational Sciences, School of Dental Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Lannawill Caruth
    Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Ganesh Chandrasekaran
    Department of Computer and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India.
  • Andrew Cucchiara
    Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Michael J Kallan
    Center for Clinical Epidemiology and Biostatistics (CCEB), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Lynn Martin
    Department of Basic & Translational Sciences, School of Dental Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Magda Feres
    Department of Periodontology, Guarulhos University, Guarulhos, SP, Brazil.
  • Kyle Bittinger
    Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
  • Kimon Divaris
    Department of Pediatric Dentistry and Dental Public Health, Adams School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, USA.
  • Joseph Glessner
    Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
  • Alpdogan Kantarci
    Harvard School of Dental Medicine, Boston, Massachusetts, USA.
  • William Giannobile
    Department of Oral Medicine, Infection, and Immunity, Harvard School of Dental Medicine, Boston, Massachusetts, USA.
  • Shefali Setia Verma
    Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Flavia Teles
    Department of Basic & Translational Sciences, School of Dental Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

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