ArticleHealth science reports2024
Perspectives toward the application of Artificial Intelligence in anesthesiology-related practices in Saudi Arabia: A cross-sectional study of physicians views.
Article in Health science reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Generative AI in perioperative medicine and anesthesiology: ethical integration, educational innovation, and the future of clinical professionalism.Journal of anesthesia · 2026Review
- National Assessment of Emergency, Intensive Care, and Anesthesia Physician Distribution in Saudi Arabia, 2023: Implications for Emergency Care Access.Emergency medicine international · 2026Article
- Nursing Students' Perspectives on Integrating Artificial Intelligence Into Clinical Practice and Training: A Qualitative Descriptive Study.Health science reports · 2025Article
- Perspectives toward the application of Artificial Intelligence in anesthesiology-related practices in Saudi Arabia: A cross-sectional study of physicians views.Health science reports · 2024Article
- The use of artificial intelligence in anesthesiology: Attitudes and ethical concerns of anesthesiologists.Saudi journal of anaesthesiaArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: The use of Artificial Intelligence (AI) relies on computer science and large datasets, with the technology mimicking human intelligence as it makes logical decisions. This study aims to assess the perceptions and experiences of anesthesiology practitioners toward AI and identify its benefits to healthcare professionals and patients, along with current and future applications of AI. Methods: This cross-sectional descriptive online survey study was disseminated to physicians who work in anesthesiology practice in Saudi Arabia. Descriptive statistics were used to report the characteristics of the respondents and summarize the results of the survey. Results: There were 109 responses, with 85.32% being male, 35.78% being aged 40-49 years, and 69.72% being consultant anesthesiologists. The majority of participants (73.39%) believed that AI could be used in multiple settings related to anesthesiology practice. Participants also believed that AI could facilitate access to data (76.15%), enable precise decision-making (75.23%), reduce medical errors (55.04%), reduce workload and shortage of healthcare personnel (53.21%), and allow healthcare personnel to focus on more demanding cases (69.72%). In addition, the majority of participants believed that AI can be beneficial to patients, in which 69.72% believed that AI can improve patient access to care, 77.06% believed that AI can facilitate patient education, and 65.14% believed that AI can guide patients during treatment. Lastly, 70.64% believed that AI would be beneficial to anesthesiology practices in the future. However, 61.47% claimed that their workplace has no plan for adopting AI. Conclusions: The anesthesiologists showed generally positive attitudes towards AI, in spite of its limited utilization and implementation challenges. Strong beliefs exist about AI's future potential in anesthesia care and postgraduate education.
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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.