Evidence map›Paper›PMID 39310597›Full record

ArticleCureus2024

Utilization of Artificial Intelligence (AI) in Healthcare Decision-Making Processes: Perceptions of Caregivers in Saudi Arabia.

Horaya A Amin, Turki M Alanzi

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

2 authors.

Horaya A AminPublic Health, Imam Abdulrahman Bin Faisal University, Dammam, SAU.
Turki M AlanziHealth Information Management and Technology, Imam Abdulrahman Bin Faisal University, Dammam, SAU.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background In the evolving landscape of healthcare, artificial intelligence (AI) has emerged as a transformative force, revolutionizing decision-making processes. Through advanced machine learning and data analytics, AI promises precision and personalized treatments, particularly impactful in diagnostics and personalized medicine. Aim and objectives This study aims to investigate the utilization and effectiveness of AI algorithms among healthcare caregivers, focusing on decision-making processes. Objectives include assessing AI adoption prevalence, understanding demographic factors influencing utilization, and evaluating its impact on decision-making dynamics, diagnostics, and personalized medicine. Methods Employing a quantitative cross-sectional approach, an online questionnaire was distributed to 224 healthcare professionals. The survey covered AI familiarity, perceived effectiveness, and potential barriers. Data analysis utilized descriptive statistics and bivariate analyses. Results Seventy-five percent of caregivers reported that they used AI in the decision-making process, with nurses representing a significant majority (50.4%). Bivariate analyses identified correlations between AI utilization and demographic variables, emphasizing its diverse adoption across specialties. Conclusion This study reveals substantial AI adoption, notably among nurses, indicating a transformative shift in decision-making processes. The findings underscore AI's potential in diagnostics and personalized medicine, highlighting the need for targeted interventions and collaborative efforts to address challenges and maximize AI benefits in healthcare.

Indexed as

artificial intelligencedecision-makinghealthcareproviderssaudi arabiautilization

Identifiers

PMID39310597
PMCPMC11416819

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.