Artificial intelligence and machine learning in diagnosing and managing temporomandibular disorders: A systematic review and meta-analysis.

ABSTRACT:

Background

Artificial intelligence (AI) and machine learning (ML) models have recently emerged as promising tools for enhancing diagnostic accuracy.

Objective

To evaluate the diagnostic accuracy of AI/ML models in detecting TMDs through a systematic review and meta-analysis of existing literature.

Methods

A comprehensive search of electronic databases was conducted to identify studies assessing the diagnostic performance of AI/ML models in TMD diagnosis (PROSPERO-CRD420251035080). Data extraction and quality assessment were conducted independently by two reviewers using the AXIS tool for cross-sectional and Newcastle-Ottawa Scale for cohort studies. Meta-analysis of diagnostic accuracy was performed using pooled sensitivity, specificity, diagnostic odds ratio, and are

SUBMITTER: Rajaraman V 

PROVIDER: S-EPMC12495322 | biostudies-literature | 2025 Nov-Dec

REPOSITORIES: biostudies-literature