Evidence map›Paper›PMID 40066464›Full record

ArticleFrontiers in pediatrics2025

Role of artificial intelligence in pediatric intensive care: a survey of healthcare staff perspectives in Saudi Arabia.

Khouloud Abdulrhman Al-Sofyani

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2025. 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. Article
  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

1 author.

Khouloud Abdulrhman Al-SofyaniDepartment of Pediatric, Pediatric Critical Care Unit, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial Intelligence (AI) has the potential to revolutionize Pediatric Intensive Care Units (PICUs) by enhancing diagnostic accuracy, improving patient outcomes, and streamlining routine tasks. However, integrating AI into PICU environments poses significant ethical and data privacy challenges, necessitating effective governance and robust regulatory frameworks to ensure safe and ethical implementation. This study aimed to explore valuable insights into healthcare professionals' current perceptions and readiness to adopt AI in pediatric critical care, highlighting the opportunities and challenges ahead. Methods: A cross-sectional study conducted an online survey among healthcare practitioners at King Abdulaziz University Hospital in Jeddah, Saudi Arabia. The survey included questions about professional roles, experience, and familiarity with AI, their opinions on AI's role, trust in AI-driven decisions, and ethical and privacy concerns. Statistical analyses were performed using IBM SPSS. Results: Results found varying familiarity with AI among healthcare professionals, with many expressing limited knowledge of AI applications in PICU settings. Despite this, there was growing recognition of AI's current applications. Trust in AI-driven decisions for PICU management was mixed, with most expressing partial trust. Opinions on AI's role in enhancing diagnostic accuracy and improving patient outcomes varied. Ethical considerations, data privacy, and effective governance to address regulatory and ethical challenges were highlighted as critical concerns. Conclusion: Healthcare practitioners in the PICU preferred using AI for routine patient monitoring but had concerns about its use in diagnoses and advanced healthcare. Concerns were held regarding data privacy, security breaches, and patient confidentiality.

Indexed as

artificial intelligenceethical concernshealthcarepediatric intensive care unitsurvey

Identifiers

PMID40066464
PMCPMC11891184

What OpenQuestion holds

Textmetadata
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.