Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos

Sunmoo Yoon; Michelle Odlum; Yeonsuk Lee; Thomas Choi; Ian M. Kronish; Karina W. Davidson; Joseph Finkelstein

doi:10.3233/978-1-61499-880-8-241

Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos

Sunmoo Yoon, Michelle Odlum, Yeonsuk Lee, Thomas Choi, Ian M. Kronish, Karina W. Davidson, Joseph Finkelstein

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

8 Scopus citations

Abstract

We applied deep learning algorithms to build correlate models that predict tooth mobility in a convenience sample of urban Latinos. Our application of deep learning identified age, general health, soda consumption, flossing, financial stress, and years living in the US as the strongest correlates of self-reported tooth mobility among 78 variables entered. The application of deep learning was useful for gaining insights into the most important modifiable and non-modifiable factors predicting tooth mobility, and maybe useful for guiding targeted interventions in urban Latinos.

Original language	English
Title of host publication	Data, Informatics and Technology
Subtitle of host publication	An Inspiration for Improved Healthcare
Editors	Joseph Liaskos, Mowafa S. Househ, Parisis Gallos, Arie Hasman, John Mantas
Publisher	IOS Press
Pages	241-244
Number of pages	4
ISBN (Electronic)	9781614998792
DOIs	https://doi.org/10.3233/978-1-61499-880-8-241
State	Published - 2018
Externally published	Yes

Publication series

Name	Studies in Health Technology and Informatics
Volume	251
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Keywords

Latinos
Tooth mobility
aging
deep learning
symptom science

Access to Document

10.3233/978-1-61499-880-8-241

Cite this

Yoon, S., Odlum, M., Lee, Y., Choi, T., Kronish, I. M., Davidson, K. W., & Finkelstein, J. (2018). Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos. In J. Liaskos, M. S. Househ, P. Gallos, A. Hasman, & J. Mantas (Eds.), Data, Informatics and Technology: An Inspiration for Improved Healthcare (pp. 241-244). (Studies in Health Technology and Informatics; Vol. 251). IOS Press. https://doi.org/10.3233/978-1-61499-880-8-241

Yoon, Sunmoo ; Odlum, Michelle ; Lee, Yeonsuk et al. / Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos. Data, Informatics and Technology: An Inspiration for Improved Healthcare. editor / Joseph Liaskos ; Mowafa S. Househ ; Parisis Gallos ; Arie Hasman ; John Mantas. IOS Press, 2018. pp. 241-244 (Studies in Health Technology and Informatics).

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title = "Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos",

abstract = "We applied deep learning algorithms to build correlate models that predict tooth mobility in a convenience sample of urban Latinos. Our application of deep learning identified age, general health, soda consumption, flossing, financial stress, and years living in the US as the strongest correlates of self-reported tooth mobility among 78 variables entered. The application of deep learning was useful for gaining insights into the most important modifiable and non-modifiable factors predicting tooth mobility, and maybe useful for guiding targeted interventions in urban Latinos.",

keywords = "Latinos, Tooth mobility, aging, deep learning, symptom science",

author = "Sunmoo Yoon and Michelle Odlum and Yeonsuk Lee and Thomas Choi and Kronish, {Ian M.} and Davidson, {Karina W.} and Joseph Finkelstein",

year = "2018",

doi = "10.3233/978-1-61499-880-8-241",

language = "English",

series = "Studies in Health Technology and Informatics",

publisher = "IOS Press",

pages = "241--244",

editor = "Joseph Liaskos and Househ, {Mowafa S.} and Parisis Gallos and Arie Hasman and John Mantas",

booktitle = "Data, Informatics and Technology",

address = "United States",

}

Yoon, S, Odlum, M, Lee, Y, Choi, T, Kronish, IM, Davidson, KW & Finkelstein, J 2018, Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos. in J Liaskos, MS Househ, P Gallos, A Hasman & J Mantas (eds), Data, Informatics and Technology: An Inspiration for Improved Healthcare. Studies in Health Technology and Informatics, vol. 251, IOS Press, pp. 241-244. https://doi.org/10.3233/978-1-61499-880-8-241

Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos. / Yoon, Sunmoo; Odlum, Michelle; Lee, Yeonsuk et al.
Data, Informatics and Technology: An Inspiration for Improved Healthcare. ed. / Joseph Liaskos; Mowafa S. Househ; Parisis Gallos; Arie Hasman; John Mantas. IOS Press, 2018. p. 241-244 (Studies in Health Technology and Informatics; Vol. 251).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Davidson, Karina W.

AU - Finkelstein, Joseph

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AB - We applied deep learning algorithms to build correlate models that predict tooth mobility in a convenience sample of urban Latinos. Our application of deep learning identified age, general health, soda consumption, flossing, financial stress, and years living in the US as the strongest correlates of self-reported tooth mobility among 78 variables entered. The application of deep learning was useful for gaining insights into the most important modifiable and non-modifiable factors predicting tooth mobility, and maybe useful for guiding targeted interventions in urban Latinos.

KW - Latinos

KW - Tooth mobility

KW - aging

KW - deep learning

KW - symptom science

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BT - Data, Informatics and Technology

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PB - IOS Press

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Yoon S, Odlum M, Lee Y, Choi T, Kronish IM, Davidson KW et al. Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos. In Liaskos J, Househ MS, Gallos P, Hasman A, Mantas J, editors, Data, Informatics and Technology: An Inspiration for Improved Healthcare. IOS Press. 2018. p. 241-244. (Studies in Health Technology and Informatics). doi: 10.3233/978-1-61499-880-8-241

Applying Deep Learning to Understand Predictors of Tooth Mobility among Urban Latinos

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