Evidence map›Paper›PMID 38076258›Full record

ArticleFrontiers in medicine2023

The application of artificial intelligence in diabetic retinopathy screening: a Saudi Arabian perspective.

Abdulaziz A Barakat, Omar Mobarak, Haroon Ahmed Javaid, Mhd Rasheed Awad, Karam Hamweyah, Abderrahman Ouban, Selwa A F Al-Hazzaa

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. 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

7 authors at 2 institutions in 1 country.

Abdulaziz A BarakatCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Omar MobarakCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Haroon Ahmed JavaidCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Mhd Rasheed AwadCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Karam HamweyahCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Abderrahman OubanCollege of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
Selwa A F Al-HazzaaKing Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia.
Alfaisal University · SAKing Abdulaziz City for Science and Technology · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Diabetic retinopathy (DR) is the leading cause of preventable blindness in Saudi Arabia. With a prevalence of up to 40% of patients with diabetes, DR constitutes a significant public health burden on the country. Saudi Arabia has not yet established a national screening program for DR. Mounting evidence shows that Artificial intelligence (AI)-based DR screening programs are slowly becoming superior to traditional screening, with the COVID-19 pandemic accelerating research into this topic as well as changing the outlook of the public toward it. The main objective of this study is to evaluate the perception and acceptance of AI in DR screening among eye care professionals in Saudi Arabia. Methods: A cross-sectional study using a self-administered online-based questionnaire was distributed by email through the registry of the Saudi Commission For Health Specialties (SCFHS). 309 ophthalmologists and physicians involved in diabetic eye care in Saudi Arabia participated in the study. Data analysis was done by SPSS, and a value of Results: 54% of participants rated their level of AI knowledge as above average and 63% believed that AI and telemedicine are interchangeable. 66% believed that AI would decrease the workforce of physicians. 79% expected clinical efficiency to increase with AI. Around 50% of participants expected AI to be implemented in the next 5 years. Discussion: Most participants reported good knowledge about AI. Physicians with more clinical experience and those who used e-health apps in clinical practice regarded their AI knowledge as higher than their peers. Perceived knowledge was strongly related to acceptance of the benefits of AI-based DR screening. In general, there was a positive attitude toward AI-based DR screening. However, concerns related to the labor market and data confidentiality were evident. There should be further education and awareness about the topic.

Indexed as

artificial intelligenceCOVID-19diabetic retinopathyophthalmologypandemicSaudi Arabiascreening

Identifiers

PMID38076258
PMCPMC10703427
OpenAlexW4388946554

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.