Evidence map›Paper›PMID 35082362›Full record

ArticleScientific reports2022

Genetic data sharing and artificial intelligence in the era of personalized medicine based on a cross-sectional analysis of the Saudi human genome program.

Abdulmajeed F Alrefaei, Yousef M Hawsawi, Deyab Almaleki, Tarik Alafif, Faisal A Alzahrani, Muhammed A Bakhrebah

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Review
  11. Egypt Genome: Towards an African new genomic era.Journal of advanced research · 2025
    Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Core elements of participant consent documents for Canadian human genomics research and the National Human Genome Library: guidance for policy.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2022
    Article
  20. 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

6 authors.

Abdulmajeed F AlrefaeiDepartment of Biology, Genetic and Molecular Biology Central Lab, Jamoum University College, Umm Al-Qura University, Makkah, 21955, Saudi Arabia. afrefaei@uqu.edu.sa.
Yousef M HawsawiResearch Centre, King Faisal Specialist Hospital and Research Centre, P.O. Box 40047, Jeddah, 21499, Saudi Arabia.
Deyab AlmalekiDepartment of Evaluation, Measurement, and Research, Umm Al-Qura University, Makkah, 21955, Saudi Arabia.
Tarik AlafifComputer Science Department, Jamoum University College, Umm Al-Qura University, Jamoum, 25375, Saudi Arabia.
Faisal A AlzahraniDepartment of Biochemistry, Faculty of Science, Embryonic Stem Cells Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Muhammed A BakhrebahKing Abdulaziz City for Science and Technology (KACST), Life Science and Environment Research Institute, P.O. Box 6086, Riyadh, 11442, Saudi Arabia.

Funding

King Abdulaziz University FP-53-42
6 · The paper itself

Abstract

The success of the Saudi Human Genome Program (SHGP), one of the top ten genomic programs worldwide, is highly dependent on the Saudi population embracing the concept of participating in genetic testing. However, genetic data sharing and artificial intelligence (AI) in genomics are critical public issues in medical care and scientific research. The present study was aimed to examine the awareness, knowledge, and attitude of the Saudi society towards the SHGP, the sharing and privacy of genetic data resulting from the SHGP, and the role of AI in genetic data analysis and regulations. Results of a questionnaire survey with 804 respondents revealed moderate awareness and attitude towards the SHGP and minimal knowledge regarding its benefits and applications. Respondents demonstrated a low level of knowledge regarding the privacy of genetic data. A generally positive attitude was found towards the outcomes of the SHGP and genetic data sharing for medical and scientific research. The highest level of knowledge was detected regarding AI use in genetic data analysis and privacy regulation. We recommend that the SHGP's regulators launch awareness campaigns and educational programs to increase and improve public awareness and knowledge regarding the SHGP's benefits and applications. Furthermore, we propose a strategy for genetic data sharing which will facilitate genetic data sharing between institutions and advance Personalized Medicine in genetic diseases' diagnosis and treatment.

Indexed as

Artificial IntelligenceHealth Knowledge, Attitudes, PracticeAdolescentAdultCross-Sectional StudiesFemaleGenetic TestingGenome, HumanHumansInformation DisseminationMaleMiddle AgedPrecision MedicineSaudi ArabiaSurveys and Questionnaires

Identifiers

PMID35082362
PMCPMC8791994

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.