Evidence map›Paper›PMID 34312593›Full record

ArticleMaterials today. Proceedings2023

The artificial intelligence (AI) role for tackling against COVID-19 pandemic.

Ali H Shamman, Ahmed A Hadi, Ali R Ramul, Musaddak M Abdul Zahra, Hassan M Gheni

Abstract read
In one paragraph

Article in Materials today. Proceedings, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Ali H ShammanComputer Techniques Engineering Department, Al-Mustaqbal University College, Hilla, Babil, Iraq.
Ahmed A HadiComputer Techniques Engineering Department, Al-Mustaqbal University College, Hilla, Babil, Iraq.
Ali R RamulComputer Techniques Engineering Department, Al-Mustaqbal University College, Hilla, Babil, Iraq.
Musaddak M Abdul ZahraComputer Techniques Engineering Department, Al-Mustaqbal University College, Hilla, Babil, Iraq.
Hassan M GheniComputer Techniques Engineering Department, Al-Mustaqbal University College, Hilla, Babil, Iraq.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 gains from the research and technology component's establishment of information science, artificial intelligence, and computer understanding. The article aims to discuss the numerous facets of today's modern technology utilized to combat COVID-19 emergencies on various scales, such as medicinal picture handling, illness tracking, expected outcomes, computational science, and medications. Techniques: A complex search of the knowledge base associated with existing COVID-19 innovation is conducted. Furthermore, a concise survey of the excluded data is conducted, analyzing the various aspects of current developments for dealing with the COVID-19 pandemic. The below are the outcomes: We have a window of musings on the audit of the tech propellers used to mitigate and mask the significant impact of the upheaval. Even though several investigations into current innovation in COVID-19 have surfaced, there are still required implementations and contributions of innovation in this war. Consequently, a thorough presentation of the available data is given, and several modern technology implementations for combating the pandemic of COVID-19. Continuous advancements of advanced technologies have aided in improving the public's lives, and there is a strong belief that proven study plans utilizing AI would be of great benefit in assisting people in combating this infection.

Indexed as

Artificial intelligenceCOVID-19Machine learningModern technology

Identifiers

PMID34312593
PMCPMC8295009

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.