Evidence map›Paper›PMID 34391673›Full record

ArticleResearch in social & administrative pharmacy : RSAP2022

Incessant threat of COVID-19 variants: Highlighting need for a mix of FDA-approved artificial intelligence tools and community pharmacy services.

Muhammad Faisal Nadeem, Nazish Matti, Shagufta Parveen, Sehrish Rafiq

Abstract read
In one paragraph

Article in Research in social & administrative pharmacy : RSAP, 2022. 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
–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

2 citing papers in PubMed.

  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.

Muhammad Faisal NadeemUniversity of Veterinary and Animal Sciences, Lahore, Punjab, Pakistan. Electronic address: faisal.nadeem@uvas.edu.pk.
Nazish MattiDepartment of Pharmacy, Quaid-i-Azam University, Islamabad, Pakistan. Electronic address: nazish341@yahoo.com.
Shagufta ParveenInstitute of Agricultural Science, University of the Punjab, Lahore, Pakistan. Electronic address: shagufta06@yahoo.com.
Sehrish RafiqZiauddin University, Karachi, Pakistan. Electronic address: Sehrish.rafiq133@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Seamless integration of artificial intelligence (AI) technology, especially FDA-approved AI tools, in community pharmacies can build increasingly effective and easy care pathways, thereby minimizing burden on healthcare system, and ensuring compliance to preventive measure through limiting hospital visits. In this regard, the WHO needs to enlist and provide guidance on most promising AI tools that can be implemented in community pharmacy settings.

Indexed as

Community Pharmacy ServicesCOVID-19Artificial IntelligenceHumansSARS-CoV-2

Identifiers

PMID34391673
PMCPMC8294695

What OpenQuestion holds

Textmetadata
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.