Evidence map›Paper›PMID 41538502›Full record

ArticleDental press journal of orthodontics2026

Clinical decisions in Orthodontics using x-ray-based images and artificial intelligence approaches: a scoping review.

Pedro Henrique José de Oliveira, João Roberto Gonçalves, Luiz Gonzaga Gandini Júnior, Julianna de Oliveira Lima Parizotto, Michelle Sousa Oliveira, Renata Mayumi Kato, Karine Evangelista, Lucia Helena Soares Cevidanes, Jonas Bianchi

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in Dental press journal of orthodontics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

9 authors.

Pedro Henrique José de OliveiraSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0000-0002-0422-5149
João Roberto GonçalvesSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0000-0002-4935-2256
Luiz Gonzaga Gandini JúniorSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0000-0001-8656-6010
Julianna de Oliveira Lima ParizottoSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0000-0001-5557-4333
Michelle Sousa OliveiraSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0009-0006-8984-2635
Renata Mayumi KatoSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0000-0002-7806-1167
Karine EvangelistaFederal University of Goiás, Dental School, Department of Orthodontics (Goiânia/GO, Brazil).ORCID http://orcid.org/0000-0003-0258-9739
Lucia Helena Soares CevidanesUniversity of Michigan, Dental School, Department of Orthodontics and Pediatric Dentistry (Michigan, USA).ORCID http://orcid.org/0000-0001-9786-2253
Jonas BianchiSão Paulo State University, Dental School, Department of Morphology, Genetics, Orthodontics and Pediatric Dentistry (Araraquara/SP, Brazil).ORCID http://orcid.org/0000-0002-3749-0918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionArtificial intelligence (AI) in health has increased its applications over the last years. The large amount of data available due to the improvement of data storage and digital exams provided better knowledge in treatment planning and opened new possibilities of applications of AI in Orthodontics' diagnosis and treatment planning.

objectiveThe aim of this scoping review was to examine when AI models enhance the clinical decision-making process in orthodontic diagnosis and treatment planning, with a focus on the utilization of X-ray-based imaging.

methodsIndividual eletronic search strategies were developed and conducted on PubMed/Medline, Scopus, Web fo Science, Embase, Lilacs, and Cochrane Library (only English language articles published from January 2000 to October 20, 2021), aiming for relevant studies that met the eligibility criteria.

results12 studies were included, categorized in 5 different groups: Orthognathic surgery, Temporomandibular Joint (TMJ) osteoarthritis, skeletal pattern, obstructive sleep apnea (OSA), and skeletal maturation/development. Most of the AI models used were Deep Learning (DL) based and the X-ray image that was most used was lateral radiographs.

conclusionIntegrating AI into clinical practice will likely continue to evolve, enhancing treatment planning in selective cases. The best applications were over TMJ osteoarthritis, skeletal maturation, and classification, OSA, and the need for orthognathic surgery.

Indexed as

Artificial IntelligenceClinical Decision-MakingOrthodonticsHumansOsteoarthritisPatient Care PlanningSleep Apnea, ObstructiveTemporomandibular Joint Disorders

Identifiers

PMID41538502
PMCPMC12788498

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Registered trials

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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.