Early Childhood Caries Classifier

The ECC classifier uses information on several early childhood oral health-related domains and computes the likelihood of being an ECC case. It uses an automated machine learning (AutoML) algorithm that was developed using data from the ZOE 2.0 study and the NHANES 2011-2018 clinical examination data. Read more about the development, evaluation, and deployment approach in Karhade et al. (manuscript in press). The work is supported by a grant from the National Institute of Dental and Craniofacial Research (NIDCR: U01DE025046; PI: Kimon Divaris).

Individual data entry Batch data entry

Below enter either the child’s age in months or their date of birth, which will then used to calculate age in months based on today’s date.

Age in Months:
Parent-reported child oral health status:
Poor Fair Good Very good Excellent

Probability of being an ECC case

{{ probA }} or {{ probA * 100 }}%

Probability of not being an ECC case

{{ probB }} or {{ probB * 100 }}%

Likelihood ratio of being an ECC case

{{ lr }}

Coming Soon

Fluoridated Toothpaste
Dental Home
Toothbrushing Frequency
Fluoridated Water
Adult involvement in toothbrushing
History of bottle in bed
Daily frequency of sugar-containing snacks/beverages
Residential Zip Code (US only)
Child is eligible for public insurance (e.g. Medicaid)
Upload photographs of the child’s dentition