Artificial Intelligence-Assisted Analysis of Prevalence Patterns and Phenotypic Distribution of Dental Pulp Stones Using Cone-Beam Computed Tomography Imaging. Journal Abstract - Guideline Central

Artificial Intelligence-Assisted Analysis of Prevalence Patterns and Phenotypic Distribution of Dental Pulp Stones Using Cone-Beam Computed Tomography Imaging.

Published: 2026 Mar 01

Authors

, , ,

Abstract

Artificial intelligence (AI) is increasingly being integrated into dental radiology to enhance diagnostic accuracy and support epidemiological research. AI-driven techniques, such as K-Means clustering and principal component analysis (PCA) offer novel approaches for analyzing cone-beam computed tomography (CBCT) data.

Keywords: Artificial intelligence, K-means clustering, cone-beam computed tomography, dental radiology, phenotype, prevalence patterns, principal component analysis, pulp stones, risk stratification

Source

Nigerian journal of clinical practice

Publication Type

Journal Article

Language

English

PubMed ID

41912461

MeSH terms

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