Using machine learning algorithms to investigate factors associated with complete edentulism among older adults in the United States.
BRFSS
machine learning
older adults
tooth loss
Journal
Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry
ISSN: 1754-4505
Titre abrégé: Spec Care Dentist
Pays: United States
ID NLM: 8103755
Informations de publication
Date de publication:
07 Feb 2023
07 Feb 2023
Historique:
revised:
10
01
2023
received:
02
06
2022
accepted:
19
01
2023
entrez:
7
2
2023
pubmed:
8
2
2023
medline:
8
2
2023
Statut:
aheadofprint
Résumé
Edentulism is an incapacitating condition, and its prevalence is unequal among different population groups in the United States (US) despite its declining prevalence. This study aimed to investigate the current prevalence, apply Machine Learning (ML) Algorithms to investigate factors associated with complete tooth loss among older US adults, and compare the performance of the models. The cross-sectional 2020 Behavioral Risk Factor Surveillance System (BRFSS) data was used to evaluate the prevalence and factors associated with edentulism. ML models were developed to identify factors associated with edentulism utilizing seven ML algorithms. The performance of these models was compared using the area under the receiver operating characteristic curve (AUC). An overall prevalence of 11.9% was reported. The AdaBoost algorithm (AUC = 84.9%) showed the best performance. Analysis showed that the last dental visit, educational attainment, smoking, difficulty walking, and general health status were among the top factors associated with complete edentulism. Findings from our study support the declining prevalence of complete edentulism in older adults in the US and show that it is possible to develop a high-performing ML model to investigate the most important factors associated with edentulism using nationally representative data.
Types de publication
Journal Article
Langues
eng
Informations de copyright
© 2023 The Authors. Special Care in Dentistry published by Special Care Dentistry Association and Wiley Periodicals LLC.
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