Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7
by
Shen, Jie
, Ramos-Gomez, Francisco
, Maida, Carl A.
, Kinsler, Janni J.
, Marcus, Marvin
, Hays, Ron D.
, Xiong, Di
, Liu, Honghu
, Lee, Steve Y.
, Crall, James J.
, Wang, Yan
in
Age
/ Agreements
/ Algorithms
/ Children
/ Children & youth
/ COVID-19
/ Decision trees
/ Dental care
/ Dental caries
/ Dentists
/ disparities
/ Health care
/ Health education
/ Infectious diseases
/ Learning algorithms
/ Machine learning
/ machine learning algorithms
/ oral health
/ Oral hygiene
/ Pandemics
/ Parents
/ Parents & parenting
/ Pediatrics
/ Polls & surveys
/ Public health
/ Questionnaires
/ random forest
/ Screening
/ Sensitivity
/ Teeth
2021
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7
by
Shen, Jie
, Ramos-Gomez, Francisco
, Maida, Carl A.
, Kinsler, Janni J.
, Marcus, Marvin
, Hays, Ron D.
, Xiong, Di
, Liu, Honghu
, Lee, Steve Y.
, Crall, James J.
, Wang, Yan
in
Age
/ Agreements
/ Algorithms
/ Children
/ Children & youth
/ COVID-19
/ Decision trees
/ Dental care
/ Dental caries
/ Dentists
/ disparities
/ Health care
/ Health education
/ Infectious diseases
/ Learning algorithms
/ Machine learning
/ machine learning algorithms
/ oral health
/ Oral hygiene
/ Pandemics
/ Parents
/ Parents & parenting
/ Pediatrics
/ Polls & surveys
/ Public health
/ Questionnaires
/ random forest
/ Screening
/ Sensitivity
/ Teeth
2021
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7
by
Shen, Jie
, Ramos-Gomez, Francisco
, Maida, Carl A.
, Kinsler, Janni J.
, Marcus, Marvin
, Hays, Ron D.
, Xiong, Di
, Liu, Honghu
, Lee, Steve Y.
, Crall, James J.
, Wang, Yan
in
Age
/ Agreements
/ Algorithms
/ Children
/ Children & youth
/ COVID-19
/ Decision trees
/ Dental care
/ Dental caries
/ Dentists
/ disparities
/ Health care
/ Health education
/ Infectious diseases
/ Learning algorithms
/ Machine learning
/ machine learning algorithms
/ oral health
/ Oral hygiene
/ Pandemics
/ Parents
/ Parents & parenting
/ Pediatrics
/ Polls & surveys
/ Public health
/ Questionnaires
/ random forest
/ Screening
/ Sensitivity
/ Teeth
2021
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7
Journal Article
Using a Machine Learning Algorithm to Predict the Likelihood of Presence of Dental Caries among Children Aged 2 to 7
2021
Request Book From Autostore
and Choose the Collection Method
Overview
Background: Dental caries is the most common chronic childhood infectious disease and is a serious public health problem affecting both developing and industrialized countries, yet it is preventable in most cases. This study evaluated the potential of screening for dental caries among children using a machine learning algorithm applied to parent perceptions of their child’s oral health assessed by survey. Methods: The sample consisted of 182 parents/caregivers and their children 2–7 years of age living in Los Angeles County. Random forest (a machine learning algorithm) was used to identify survey items that were predictors of active caries and caries experience. We applied a three-fold cross-validation method. A threshold was determined by maximizing the sum of sensitivity and specificity conditional on the sensitivity of at least 70%. The importance of survey items to classifying active caries and caries experience was measured using mean decreased Gini (MDG) and mean decreased accuracy (MDA) coefficients. Results: Survey items that were strong predictors of active caries included parent’s age (MDG = 0.84; MDA = 1.97), unmet needs (MDG = 0.71; MDA = 2.06) and the child being African American (MDG = 0.38; MDA = 1.92). Survey items that were strong predictors of caries experience included parent’s age (MDG = 2.97; MDA = 4.74), child had an oral health problem in the past 12 months (MDG = 2.20; MDA = 4.04) and child had a tooth that hurt (MDG = 1.65; MDA = 3.84). Conclusion: Our findings demonstrate the potential of screening for active caries and caries experience among children using surveys answered by their parents.
MBRLCatalogueRelatedBooks
Related Items
Related Items
This website uses cookies to ensure you get the best experience on our website.