Evidence map›Paper›PMID 31386555›Full record

SynthesisDento maxillo facial radiology2020

The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review.

Kuofeng Hung, Carla Montalvao, Ray Tanaka, Taisuke Kawai, Michael M Bornstein

Registry-linked trialAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Dento maxillo facial radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07523815 (Assessment of the Accuracy of Artificial Intelligence Assisted Workflow Versus Conventional Workflow in Computer Guided Implant Placement), which is not on this map. Cited by 174 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
174citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07523815 phase4recruitingnot on this mapstarted 2026, after this paper: background citation

Assessment of the Accuracy of Artificial Intelligence Assisted Workflow Versus Conventional Workflow in Computer Guided Implant Placement: A Randomized Controlled Clinical Trial.

TypeinterventionalSponsorSandra Moussa Botros El TarziRan2026 to 2026Enrolled20ConditionsPartially Edentulous MandibleArmsAI assisted implant placement, Conventional computer guided implant placement
3 · Its place in the literature

Who cites it

174 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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  4. Diagnostic accuracy of artificial intelligence models in detecting osteoporosis using dental images: a systematic review and meta-analysis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025
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114 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kuofeng HungOral and Maxillofacial Radiology, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Carla MontalvaoOral and Maxillofacial Radiology, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Ray TanakaOral and Maxillofacial Radiology, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.
Taisuke KawaiDepartment of Oral and Maxillofacial Radiology, School of Life Dentistry at Tokyo, Nippon Dental University, Tokyo, Japan.
Michael M BornsteinOral and Maxillofacial Radiology, Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR, China.ORCID http://orcid.org/0000-0002-7773-8957

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the current clinical applications and diagnostic performance of artificial intelligence (AI) in dental and maxillofacial radiology (DMFR).

methodsStudies using applications related to DMFR to develop or implement AI models were sought by searching five electronic databases and four selected core journals in the field of DMFR. The customized assessment criteria based on QUADAS-2 were adapted for quality analysis of the studies included.

resultsThe initial electronic search yielded 1862 titles, and 50 studies were eventually included. Most studies focused on AI applications for an automated localization of cephalometric landmarks, diagnosis of osteoporosis, classification/segmentation of maxillofacial cysts and/or tumors, and identification of periodontitis/periapical disease. The performance of AI models varies among different algorithms.

conclusionThe AI models proposed in the studies included exhibited wide clinical applications in DMFR. Nevertheless, it is still necessary to further verify the reliability and applicability of the AI models prior to transferring these models into clinical practice.

Indexed as

Artificial IntelligenceRadiography, DentalRadiologyAlgorithmsHumansReproducibility of Resultsartificial intelligencecomputer-assisteddentistrydiagnostic imagingradiography

Identifiers

PMID31386555
PMCPMC6957072

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.