Evidence map›Paper›PMID 36259008›Full record

ReviewCureus2022

Role of Technology in Detection of COVID-19.

Drishti V Lohiya, Swanand S Pathak

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Drishti V LohiyaMedicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND.
Swanand S PathakPharmacology, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND.
Datta Meghe Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus caused coronavirus infection termed as COVID-19, an illness that has spread devastation all over the world. It was developed first in China and had swiftly spread throughout the world. COVID has created imposed burden on health in the lives of all individuals around the globe. This article provides a number of unprecedented detection technologies used in the detection of infection. COVID has created a large number of symptoms in the young, adolescent as well as elderly population. Old age people are susceptible to fatal serious symptoms because of low immunity. With these goals in mind, this article includes substantial condemning descriptions of the majority of initiatives in order to create diagnostic tools for easy diagnosis. It also provides the reader with a multidisciplinary viewpoint on how traditional approaches such as serology and reverse transcriptase polymerase chain reaction (RT-PCR) along with the frontline techniques such as clustered regularly interspaced short palindromic repeats (CRISPR)/Cas and artificial intelligence/machine learning have been utilized to gather information. The story will inspire creative new ways for successful detection therapy and to prevent this pandemic among a wide audience of operating and aspiring biomedical scientists and engineers.

Indexed as

artificial intelligencecas systemcovidct-scanelisamolecular investigationsrt-pcrsars-cov-2serological testthermometer thermal scanners

Identifiers

PMID36259008
PMCPMC9573002
OpenAlexW4296020844

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.