Evidence map›Paper›PMID 37496534›Full record

ArticleCureus2023

Knowledge, Awareness, and Perception of COVID-19 and Artificial Intelligence: A Cross-Sectional Study Among the Population in Saudi Arabia.

Shaista Haleem, Nassreen H Albar, Mogabh S Al Fahad, Hala O AlWasem

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 3 institutions in 1 country.

Shaista HaleemAesthetic and Restorative Dentistry, Riyadh Elm University, Riyadh, SAU.
Nassreen H AlbarRestorative Dentistry, Jazan University, Jazan, SAU.
Mogabh S Al FahadDentistry, King Saud University, Riyadh, SAU.
Hala O AlWasemDentistry, Riyadh Elm University, Riyadh, SAU.
Jazan University · SAKing Saud University · SARiyadh Elm University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) has made significant contributions to the development of medicines and vaccines. In addition, AI can analyze large amounts of COVID-19 test data, including the number of positive cases, to forecast the trajectory of the pandemic.

aimThis study aimed to assess the knowledge, perception, and awareness of the general population in Saudi Arabia regarding AI and its application in combating COVID-19.

methodsA cross-sectional research design was employed, and online surveys were distributed via email and social media platforms. Purposeful sampling was used to select participants who met the inclusion criteria. The reliability and validity of the survey instrument were also assessed.

resultsThe majority of respondents (34.6%) fell within the age range of 30 to 39 years. The sample predominantly consisted of female participants. Approximately 59% of respondents reported using at least one AI tool or application on a daily basis. Furthermore, the majority of respondents agreed that digital medical services, mentioned in a previous question, could be beneficial in reducing unnecessary interactions between patients and healthcare providers.

conclusionThe COVID-19 pandemic has demonstrated the transformative potential of AI in pandemic response. AI has played a crucial role in various aspects of combating COVID-19, including patient diagnosis, treatment development, and vaccine creation. However, challenges and limitations exist in terms of data accessibility, bias, and privacy when utilizing AI. These issues need to be addressed to ensure the ethical and responsible use of AI in the fight against COVID-19 and future pandemics.

Indexed as

artificial intelligencecovid-19machine learningsaudi arabiasurvey

Identifiers

PMID37496534
PMCPMC10368304
OpenAlexW4381988647

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.