Evidence map›Paper›PMID 35206998›Full record

ReviewHealthcare (Basel, Switzerland)2022

Telehealth and Artificial Intelligence Insights into Healthcare during the COVID-19 Pandemic.

Dina M El-Sherif, Mohamed Abouzid, Mohamed Tarek Elzarif, Alhassan Ali Ahmed, Ashwag Albakri, Mohammed M Alshehri

Abstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 2 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

36 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
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  6. Article
  7. Adoption of Telemedicine for Dementia Care in Nigeria: Scoping Review.Interactive journal of medical research · 2025
    Review
  8. The sustainability of hospital accreditation models: a cross-sectional study.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Observational
  16. Review
  17. Article
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  20. 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

6 authors.

Dina M El-SherifNational Institute of Oceanography and Fisheries (NIOF), Cairo 11516, Egypt.ORCID 0000-0002-8798-9004
Mohamed AbouzidDepartment of Physical Pharmacy and Pharmacokinetics, Poznan University of Medical Sciences, 60-781 Poznan, Poland.ORCID 0000-0002-8917-671X
Mohamed Tarek ElzarifIndependent Digital Health Researcher and Entrepreneur, CEO Doctor Live Company, Cairo 12655, Egypt.
Alhassan Ali AhmedDoctoral School, Poznan University of Medical Sciences, 60-781 Poznan, Poland.ORCID 0000-0003-1912-0195
Ashwag AlbakriCollage of Computer Science and Information Technology, Jazan University, Jizan 45142, Saudi Arabia.ORCID 0000-0002-6356-0000
Mohammed M AlshehriMedical Research Center, Jazan University, Jizan 45142, Saudi Arabia.ORCID 0000-0003-0028-0957

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soon after the coronavirus disease 2019 pandemic was proclaimed, digital health services were widely adopted to respond to this public health emergency, including comprehensive monitoring technologies, telehealth, creative diagnostic, and therapeutic decision-making methods. The World Health Organization suggested that artificial intelligence might be a valuable way of dealing with the crisis. Artificial intelligence is an essential technology of the fourth industrial revolution that is a critical nonmedical intervention for overcoming the present global health crisis, developing next-generation pandemic preparation, and regaining resilience. While artificial intelligence has much potential, it raises fundamental privacy, transparency, and safety concerns. This study seeks to address these issues and looks forward to an intelligent healthcare future based on best practices and lessons learned by employing telehealth and artificial intelligence during the COVID-19 pandemic.

Indexed as

artificial intelligenceCOVID-19digital healthhealthcarepandemictelehealthtelemedicine

Identifiers

PMID35206998
PMCPMC8871559

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.