Evidence map›Paper›PMID 39619463›Full record

ArticleJournal of family & community medicine

The wizard of artificial intelligence: Are physicians prepared?

Osman O Radhwi, Mawyah A Khafaji

Abstract read
In one paragraph

Article in Journal of family & community medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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.

Osman O RadhwiDepartment of Hematology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Mawyah A KhafajiDepartment of Radiology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the increasing use of artificial intelligence (AI) in medicine, research into the knowledge and attitudes of medical experts toward AI is limited. This study aimed to assess physicians' attitudes and perceptions of AI applications in healthcare. MATERIALS AND

methodsA cross-sectional study was conducted at the College of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia between November 1 and December 20, 2023. Data was collected using a web-based validated self-administered questionnaire; information sought included demographics, familiarity with AI technology, attitudes towards AI applications in medicine, and perceived risks associated with its implementation. Data analysis performed using SPSS. Categorical variables were presented as frequencies and percentages, whereas mean and standard deviations were calculated for continuous variables. Four domains were used as study variables: familiarity, attitude, AI application, and possible risks. The domains were compared to the scored individual question using Pearson's correlation coefficient.

resultsA total of 128 academic staff participated (response rate 21.3%). About 41% reported being aware of AI as an emerging field and expressed desire to learn about AI. Concerns about the effect of AI on physicians' employability were not prominent. Instead, most (65.6%) agreed that new positions would be created and that the job market for those who embraced AI would increase. Thirty-two percent reported actively seeking out new technologies in their practice areas, and 24.2% would be willing to adapt AI to practice if its usefulness was published in scientific journals. Most participants (87.5%) agreed that dedicated courses would help them implement AI in their specialty. The most commonly reported problem of AI was its inability to provide opinions in unexpected scenarios. A quarter of participants believed that both AI creators and doctors should be liable for AI-caused medical errors. Physician's age, gender, or years of experience were not related to their familiarity with or attitudes toward AI.

conclusionDoctors are open to learning about AI use in medicine. Including AI learning objectives or short courses in medical curricula would help physicians develop the necessary skills for an AI-augmented healthcare system.

Indexed as

Artificial intelligenceattitudedoctorsfamiliaritytechnology

Identifiers

PMID39619463
PMCPMC11604183

What OpenQuestion holds

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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.