Evidence map›Paper›PMID 41602304›Full record

ArticleFrontiers in artificial intelligence2025

Perception and awareness of healthcare professionals toward the applications of artificial intelligence in Egyptian healthcare settings.

Shimaa Azzam, El-Morsy Ahmed El-Morsy, Amira S A Said, Nermin Eissa, Doaa Mahmoud Khalil

Abstract read
In one paragraph

Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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

5 authors.

Shimaa AzzamDepartment of Public Health Technology, Faculty of Applied Health Science Technology, Beni-Suef University, Beni-Suef, Egypt.
El-Morsy Ahmed El-MorsyDepartment of Public Health and Community Medicine, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt.
Amira S A SaidDepartment of Clinical Pharmacy, College of Pharmacy, Al Ain University, Abu Dhabi, United Arab Emirates.
Nermin EissaDepartment of Biomedical Sciences, College of Health Sciences, Abu Dhabi University, Abu Dhabi, United Arab Emirates.
Doaa Mahmoud KhalilDepartment of Public Health and Community Medicine, Faculty of Medicine, Beni-Suef University, Beni-Suef, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Healthcare professionals' awareness and handling of artificial intelligence applications in healthcare enhance patient outcomes and improve processes. This study aimed to evaluate the perception, attitude, knowledge, and practice of healthcare professionals regarding the application of artificial intelligence in Egyptian healthcare settings. Method: A cross-sectional study in which 367 healthcare professionals responded to an electronic questionnaire. Results: Out of 367 participants (234 female), radiology and lab test specialty (36.2%) was the predominant. The mean age was 27.03 years; 51.8% of respondents showed positive perception, 68.7% experienced sub-optimal knowledge, 52.9% expressed negative attitudes, and 53.4% demonstrated a low practice level of AI tools. Younger age was significantly associated with positive perception (adjusted odds ratio (AOR) = 0.905, Conclusion: Despite moderate perception, most professionals have knowledge, attitude, and practice defects. Mainly, younger age and men showed higher engagement, indicating a need for targeted AI training, especially for older and female professionals.

Indexed as

artificial intelligenceattitudehealthcareknowledgeperceptionpractice

Identifiers

PMID41602304
PMCPMC12833234

What OpenQuestion holds

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LicenceCC BY
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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.