Evidence map›Paper›PMID 38132261›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Artificial Intelligence and Its Clinical Applications in Orthodontics: A Systematic Review.

Gianna Dipalma, Alessio Danilo Inchingolo, Angelo Michele Inchingolo, Fabio Piras, Vincenzo Carpentiere, Grazia Garofoli, Daniela Azzollini, Merigrazia Campanelli, Gregorio Paduanelli, Andrea Palermo and 1 more

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 4 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.

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

43 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

11 authors.

Gianna DipalmaDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0002-5947-8987
Alessio Danilo InchingoloDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0002-6366-1039
Angelo Michele InchingoloDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0003-0104-6337
Fabio PirasDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0003-0765-7710
Vincenzo CarpentiereDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0002-3579-7342
Grazia GarofoliDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0001-6174-1978
Daniela AzzolliniDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0002-1307-8582
Merigrazia CampanelliDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0001-8445-5384
Gregorio PaduanelliDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.
Andrea PalermoImplant Dentistry College of Medicine and Dentistry Birmingham, University of Birmingham, Birmingham B46BN, UK.ORCID 0000-0002-3288-490X
Francesco InchingoloDepartment of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70124 Bari, Italy.ORCID 0000-0003-3797-5883

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review aims to analyze different strategies that make use of artificial intelligence to enhance diagnosis, treatment planning, and monitoring in orthodontics. Orthodontics has seen significant technological advancements with the introduction of digital equipment, including cone beam computed tomography, intraoral scanners, and software coupled to these devices. The use of deep learning in software has sped up image processing processes. Deep learning is an artificial intelligence technology that trains computers to analyze data like the human brain does. Deep learning models are capable of recognizing complex patterns in photos, text, audio, and other data to generate accurate information and predictions. MATERIALS AND

methodsPubmed, Scopus, and Web of Science were used to discover publications from 1 January 2013 to 18 October 2023 that matched our topic. A comparison of various artificial intelligence applications in orthodontics was generated.

resultsA final number of 33 studies were included in the review for qualitative analysis.

conclusionsThese studies demonstrate the effectiveness of AI in enhancing orthodontic diagnosis, treatment planning, and assessment. A lot of articles emphasize the integration of artificial intelligence into orthodontics and its potential to revolutionize treatment monitoring, evaluation, and patient outcomes.

Indexed as

artificial intelligencedeep learningdiagnosismachine learningorthodonticstreatment monitoringtreatment planning

Identifiers

PMID38132261
PMCPMC10743240

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.