Use of artificial intelligence for detection of MB2 canals in maxillary first molars on CBCT: a systematic review and meta-analysis.

ABSTRACT:

Background

Detecting the second mesiobuccal (MB2) canal in maxillary first molars is challenging, even with cone-beam computed tomography (CBCT). Artificial intelligence (AI), especially deep learning, has been explored as a tool to aid detection.

Objectives

This systematic review and meta-analysis evaluated the diagnostic accuracy of AI in identifying MB2 canals on CBCT.

Methods

Following PRISMA guidelines, a comprehensive electronic search across five databases (PubMed, Scopus, Web of Science, Embase, and Scopus Secondary) retrieved 52 articles. After removing duplicates and screening titles/abstracts, 7 full texts were assessed, of which 4 met the inclusion criteria. Studies were eligible if they applied AI algorithms for MB2 detection in CBCT images and reported d

SUBMITTER: Dashti M 

PROVIDER: S-EPMC12667194 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature