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).

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:

DOB:

Parent-reported child oral health status:

Poor Fair Good Very good Excellent

Submit

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

Yes

No

Dental Home

Yes

No

Toothbrushing Frequency

Twice a day or more

Once a day or less

Fluoridated Water

Yes

No

Adult involvement in toothbrushing

Yes

No

History of bottle in bed

Yes

No

Daily frequency of sugar-containing snacks/beverages

0-1

2-3

4+

Residential Zip Code (US only)

Child is eligible for public insurance (e.g. Medicaid)

Yes

No

Upload photographs of the child’s dentition