Evidence map›Paper›PMID 37153930›Full record

ReviewJournal of International Society of Preventive & Community Dentistry

Applications and Perspectives of Artificial Intelligence, Machine Learning and "Dentronics" in Dentistry: A Literature Review.

Frank Mayta-Tovalino, Arnaldo Munive-Degregori, Silvia Luza, Flor C Cárdenas-Mariño, Maria Eugenia Guerrero, John Barja-Ore

Abstract readReview
In one paragraph

Review in Journal of International Society of Preventive & Community Dentistry. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
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

6 authors.

Frank Mayta-TovalinoCHANGE Research Working Group, Faculty of Health Sciences, Universidad Cientifica del Sur, Lima, Peru.
Arnaldo Munive-DegregoriPosgraduate Department, Facultad de Letras y Humanidades, Universidad Nacional Mayor de San Marcos, Lima, Peru.
Silvia LuzaPosgraduate Department, Facultad de Letras y Humanidades, Universidad Nacional Mayor de San Marcos, Lima, Peru.
Flor C Cárdenas-MariñoPosgraduate Department, Facultad de Letras y Humanidades, Universidad Nacional Mayor de San Marcos, Lima, Peru.
Maria Eugenia GuerreroAcademic Department of Medical and Surgical Stomatology, Faculty of Dentistry, Universidad Nacional Mayor de San Marcos, Lima, Peru.
John Barja-OreAcademic Department, Dirección de Investigación, Universidad Privada del Norte, Lima, Peru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The aim of this study was to describe artificial intelligence, machine learning, and "Dentronics" applications and perspectives in dentistry. Materials and Methods: A literature review was carried out to identify the applications of artificial intelligence in the field of dentistry. A specialized search for information was carried out in three databases such as Scopus, PubMed, and Web of Science. Manuscripts published from January 1988 to November 2021 were analyzed. Articles were included without any restriction by language or country. Results: Scopus, PubMed, and Web of Science were found to have 215, 1023, and 98 registered manuscripts, respectively. Duplicates (191 manuscripts) were eliminated. Finally, 4 letters, 12 editorials, 5 books, 1 erratum, 54 conference papers, 3 conference reviews, and 222 reviews were excluded. Conclusions: Artificial intelligence has revolutionized prediction, diagnosis, and therapeutic management in modern dentistry. Finally, artificial intelligence is a potential complement to managing future data in this area.

Indexed as

Artificial intelligencemachine learningvirtual

Identifiers

PMID37153930
PMCPMC10155874

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.