Evidence map›Paper›PMID 35162751›Full record

ArticleInternational journal of environmental research and public health2022

Artificial Intelligence: A New Diagnostic Software in Dentistry: A Preliminary Performance Diagnostic Study.

Francesca De Angelis, Nicola Pranno, Alessio Franchina, Stefano Di Carlo, Edoardo Brauner, Agnese Ferri, Gerardo Pellegrino, Emma Grecchi, Funda Goker, Luigi Vito Stefanelli

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. The Potential of Artificial Intelligence in Prosthodontics: A Comprehensive Review.Medical science monitor : international medical journal of experimental and clinical research · 2024
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  8. Determination of Kennedy's classification in panoramic X-rays by automated tooth labeling.International journal of computer assisted radiology and surgery · 2025
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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

10 authors.

Francesca De AngelisDepartment of Oral and Maxillofacial Sciences, Sapienza University of Rome, Via Caserta 6, 00161 Rome, Italy.ORCID 0000-0002-7922-8870
Nicola PrannoDepartment of Oral and Maxillofacial Sciences, Sapienza University of Rome, Via Caserta 6, 00161 Rome, Italy.ORCID 0000-0003-4095-0900
Alessio FranchinaPrivate Practice, Via Legione Gallieno 44, 36100 Vicenza, Italy.ORCID 0000-0002-7679-6776
Stefano Di CarloDepartment of Oral and Maxillofacial Sciences, Sapienza University of Rome, Via Caserta 6, 00161 Rome, Italy.
Edoardo BraunerDepartment of Oral and Maxillofacial Sciences, Sapienza University of Rome, Via Caserta 6, 00161 Rome, Italy.ORCID 0000-0001-7654-482X
Agnese FerriOraland Maxillofacial Surgery Division, DIBINEM, University of Bologna, 40125 Bologna, Italy.ORCID 0000-0002-7281-1684
Gerardo PellegrinoOraland Maxillofacial Surgery Division, DIBINEM, University of Bologna, 40125 Bologna, Italy.ORCID 0000-0001-8782-8991
Emma GrecchiChirurgiche ed Odontoiatriatriche, Dipartimento di Scienze Biomediche, University of Milan, Via Della Commenda 9, 20122 Milano, Italy.ORCID 0000-0002-3417-5488
Funda GokerChirurgiche ed Odontoiatriatriche, Dipartimento di Scienze Biomediche, University of Milan, Via Della Commenda 9, 20122 Milano, Italy.ORCID 0000-0002-2354-361X
Luigi Vito StefanelliDepartment of Oral and Maxillofacial Sciences, Sapienza University of Rome, Via Caserta 6, 00161 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) has taken hold in public health because more and more people are looking to make a diagnosis using technology that allows them to work faster and more accurately, reducing costs and the number of medical errors.

methodsIn the present study, 120 panoramic X-rays (OPGs) were randomly selected from the Department of Oral and Maxillofacial Sciences of Sapienza University of Rome, Italy. The OPGs were acquired and analyzed using Apox, which takes a panoramic X-rayand automatically returns the dental formula, the presence of dental implants, prosthetic crowns, fillings and root remnants. A descriptive analysis was performed presenting the categorical variables as absolute and relative frequencies.

resultsIn total, the number of true positive (TP) values was 2.195 (19.06%); true negative (TN), 8.908 (77.34%); false positive (FP), 132 (1.15%); and false negative (FN), 283 (2.46%). The overall sensitivity was 0.89, while the overall specificity was 0.98.

conclusionsThe present study shows the latest achievements in dentistry, analyzing the application and credibility of a new diagnostic method to improve the work of dentists and the patients' care.

Indexed as

Artificial IntelligenceToothHumansItalyRadiography, PanoramicSoftwareaccuracyartificial intelligencedental radiologydigital dentistrymachine learning

Identifiers

PMID35162751
PMCPMC8835112

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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.