Evidence map›Paper›PMID 40525046›Full record

ReviewCureus2025

Exploring the Landscape of Artificial Intelligence in Saudi Arabia's Healthcare Sector: Current Trends and Challenges.

Mohammad Bayer, Amna Eisawi

Abstract readReview
In one paragraph

Review in Cureus, 2025. 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. Review
  2. Article
  3. Article
  4. Article
  5. 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.

Mohammad BayerGeneral Medicine, Glangwili General Hospital, Carmarthen, GBR.
Amna EisawiGeriatrics, Tele-Geriatric Research Fellowship, Michigan State University, East Lansing, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is advancing rapidly, and its potential to reshape the future of healthcare has been widely recognized. We conducted a review to understand the current state of AI in Saudi Arabia's healthcare sector. Our findings reveal that only 5.88% and 8.82% of major hospitals in Saudi Arabia have established specialized centers for AI and implemented AI in patient care, respectively. However, there has been a noticeable increase in academic interest, as evidenced by the growing number of research studies on the topic. Saudi Arabia's Vision 2030 aims to position the country as a global leader in healthcare. Although institutions are gradually moving toward this goal, achieving it remains a distant prospect. Therefore, healthcare institutions and stakeholders must shift their approach from a consumer-oriented mindset to one driven by innovation and invention.

Indexed as

ai in healthcareai integrationartificial intelligencehealthcare innovationsaudi arabia

Identifiers

PMID40525046
PMCPMC12168633

What Socratic 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 Socratic graph.