Evidence map›Paper›PMID 38686273›Full record

ArticleCureus2024

Artificial Intelligence in Healthcare: A Study of Physician Attitudes and Perceptions in Jeddah, Saudi Arabia.

Mahmood Alkhatieb, Abeer A Subke

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
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  4. Between Hope and Skepticism: Parent and Provider Expectations of Artificial Intelligence as a Bridge to Human-Centered Care for Children With Chronic Illness.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
  5. AI-powered tools in family medicine: Bridging technology and practice.Journal of family medicine and primary care · 2026
    Article
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  7. Article
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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.

Mahmood AlkhatiebPreventive Medicine Postgraduate Program, Saudi Ministry of Health, Jeddah, SAU.
Abeer A SubkePreventive Medicine Postgraduate Program, Saudi Ministry of Health, Jeddah, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Artificial intelligence (AI) in healthcare is rapidly advancing, reshaping diagnostic, prognostic, and operational tasks in healthcare institutions. The adoption of AI among physicians is varied, with concerns over job loss, medical errors, and lack of emotional intelligence. This study aimed to assess physicians' attitudes and perceptions toward AI in clinical practice in Jeddah, Saudi Arabia, and the factors affecting these attitudes and perceptions. Methodology A cross-sectional study was conducted among physicians at two major hospitals in Jeddah. An in-person digital survey consisted of questions regarding demographic characteristics, attitudes toward clinical AI, and perceptions of AI's impact on healthcare. Results Of the 205 participants, 76% agreed on the accuracy of AI systems, and 60% acknowledged their efficiency as a factor that could influence their willingness to use clinical AI. However, only 25.9% reported using these systems in the past year, with the majority, 74.1%, indicating they had never used them. Notably, there was a significant association between gender and attitude toward AI, with males being more likely to have a positive attitude (p = 0.01). Conclusions While the majority of participants recognized the potential benefits of AI in healthcare, its actual utilization was low. The findings suggest the need for increased AI-related training and education among physicians and the fostering of collaboration between computer scientists, engineers, and medical professionals to accelerate the development of clinically relevant AI tools.

Indexed as

artificial intelligenceattitudeshealthcareperceptionphysicians

Identifiers

PMID38686273
PMCPMC11057398

What OpenQuestion holds

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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.