Evidence map›Paper›PMID 40134414›Full record

ArticleJournal of the Saudi Heart Association2025

Perceptions of Cardiac Surgeons Regarding the Integration of Artificial Intelligence in Cardiac Surgery.

Nada Alguizzani, Fareed Khouqeer, Rasha Alorini, Imtenan Oberi

Abstract read
In one paragraph

Article in Journal of the Saudi Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Nada AlguizzaniKing Faisal University, College of Medicine, Department of Surgery, Al Ahsaa, Saudi Arabia.
Fareed KhouqeerKing Faisal Specialist Hospital and Research Centre, Department of Cardiac Surgery, Riyadh, Saudi Arabia.
Rasha AloriniUnaizah College of Medicine and Medical Sciences, Unaizah, Saudi Arabia.
Imtenan OberiCollege of Medicine, Jazan University, Jazan, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: After the surge of artificial intelligence in late 2022, researchers started exploring the idea of using artificial intelligence in the medical field. Considering the endless possibilities of artificial intelligence, there is still some hesitation toward its use in the medical field. This study aims to explore the attitudes of cardiac surgeons toward involving artificial intelligence in diagnosing cardiac conditions and planning cardiac operations. Methodology: This study surveyed cardiac surgeons on AI integration in their field using a cross-sectional design and purposive sampling. Data were collected via a structured questionnaire and analyzed in IBM SPSS 29.0. Results: Our study included 33 cardiac surgeons primarily male (n =26, 78.8 %) and Saudi nationals (n =26, 78.8 %), assessed attitudes towards AI in cardiac surgery. A significant majority supported AI for pre-operative (n =17, 51.5 %), intra-operative (n =11, 33.3 %), and post-operative tasks (n =13, 39.4 %). The overall positive attitude towards AI was 54.2 % and overall positive perception towards AI was 50 %. However, perceptions of AI's integration into healthcare varied, with the highest approval for Documentation AI Assistance (n =13, 39.40 %). No significant demographic differences were found affecting attitudes towards AI (p-values ranging from 0.576 to 1.000). Conclusion: Our study reveals a positive yet cautious attitude towards AI in cardiac surgery, recognizing its potential to improve precision and efficiency but emphasizing the irreplaceable need for human judgment and expertise in managing patient-specific variables.

Indexed as

Artificial intelligenceAttitudesCardiac surgeryPerceptions

Identifiers

PMID40134414
PMCPMC11932695

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.