Evidence map›Paper›PMID 39754101›Full record

ArticleBMC oral health2025

Knowledge, attitudes, and perceptions of a group of Egyptian dental students toward artificial intelligence: a cross-sectional study.

Marwa Elchaghaby, Reem Wahby

Registry-linked trialAbstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06348758 (Knowledge, Attitudes, And Perceptions of a Group of Egyptian Dental Students Towards Artificial Intelligence), which is not on this map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
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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.

NCT06348758 unknown statusnot on this map

Knowledge, Attitudes, And Perceptions of a Group of Egyptian Dental Students Towards Artificial Intelligence: A Cross-sectional Study

TypeobservationalSponsorCairo UniversityRan2024 to 2024Enrolled384ConditionsHealth Knowledge, Attitudes, PracticeArmsquestionnaire
3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline 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

2 authors.

Marwa ElchaghabyPediatric Dentistry and Dental Public Health, Faculty of Dentistry, Cairo University, Cairo, Egypt.ORCID 0000-0003-2414-4052
Reem WahbyPediatric Dentistry and Dental Public Health, Faculty of Dentistry, Cairo University, Cairo, Egypt. reemwahby@cu.edu.eg.ORCID 0000-0003-2285-9468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionArtificial intelligence (AI) applications have increased dramatically across a wide range of domains. Dental students will undoubtedly be impacted by the emergence of AI in dentistry.

aimThis study aimed to evaluate the knowledge, attitudes, and perceptions of a group of Egyptian dental students toward artificial intelligence. MATERIALS AND

methodAn online survey was conducted using a questionnaire sent to dental students via Google Forms. The questionnaire comprised 18 questions on participant's knowledge and perceptions regarding the future of AI in dentistry. The collected data was statistically analyzed.

resultsA total of 384 students answered the questionnaire. Of the participants, (49%) had a basic knowledge of the principles of AI, and (48%) participants were aware of AI usage in dentistry. Social media was the most common information source for AI applications. Most of the participants agreed on the leading role of AI in the advancement of dentistry and disagreed on the ability of AI to replace dentists in the future, (53%) and (44%) respectively. Moreover, (49%) and (52%) respectively of students approved the incorporation of AI applications in undergraduate and postgraduate dental training.

conclusionEgyptian dental students are acquainted with AI and its possible applications in dentistry. They consider the use of AI diagnosis exciting and approve of its definitive role in disease prediction. There is a necessity to include, enhance, and increase AI training in dental schools.

trial registrationThis study has been registered in clinical trials. gov with an identifier: NCT06348758.

Indexed as

Artificial IntelligenceStudents, DentalAdultAttitude of Health PersonnelCross-Sectional StudiesEgyptFemaleHealth Knowledge, Attitudes, PracticeHumansMaleSurveys and QuestionnairesYoung AdultAI applicationsArtificial intelligenceDental studentsDentistryKnowledgePerceptions

Identifiers

PMID39754101
PMCPMC11697735

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.