Machine Learning for Predicting Dental Caries Presence and Severity: An Age-Cohort Perspective from a Nationally Representative Survey in Brazil.
INTRODUCTION: Although preventable, dental caries remains a global public health challenge due to its multifactorial nature and the deep influence of socio-structural determinants. The non-clinical triage models demonstrated significant Net Benefit in DCA across all groups, effectively identifying high-risk individuals for prioritization without requiring clinical examination.
INTRODUCTION: Although preventable, dental caries remains a global public health challenge due to its multifactorial nature and the deep influence of socio-structural determinants. The non-clinical triage models demonstrated significant Net Benefit in DCA across all groups, effectively identifying high-risk individuals for prioritization without requiring clinical examination.
What the study was
- Study design
- Journal Article
- Population
- N=23,726
- Sample size
- 23726
- Category
- Diagnostics
- Maturity
- Exploratory
- Journal
- Caries research
Why it surfaced
Score 7/10: Journal Article, human study, Exploratory. 🟢 NEAR_TERM_IMPLEMENTABLE — Near-term implementable finding
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