Evidence map›Paper›PMID 35817176›Full record

ReviewChemosphere2022

A comparison of conventional and advanced electroanalytical methods to detect SARS-CoV-2 virus: A concise review.

Pattan-Siddappa Ganesh, Sang-Youn Kim

Open access · greenAbstract readReview
In one paragraph

Review in Chemosphere, 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
0.5field-weighted citation impact, top 36% 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, 5 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.

Pattan-Siddappa GaneshInteraction Laboratory, Advanced Technology Research Center, Future Convergence Engineering, Korea University of Technology and Education (KoreaTech), Cheonan-si, Chungcheongnam-do, 330-708, Republic of Korea. Electronic address: ganeshps11@koreatech.ac.kr.
Sang-Youn KimInteraction Laboratory, Advanced Technology Research Center, Future Convergence Engineering, Korea University of Technology and Education (KoreaTech), Cheonan-si, Chungcheongnam-do, 330-708, Republic of Korea. Electronic address: sykim@koreatech.ac.kr.
Korea University of Technology and Education · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Respiratory viruses are a serious threat to human wellbeing that can cause pandemic disease. As a result, it is critical to identify virus in a timely, sensitive, and precise manner. The present novel coronavirus-2019 (COVID-19) disease outbreak has increased these concerns. The research of developing various methods for COVID-19 virus identification is one of the most rapidly growing research areas. This review article compares and addresses recent improvements in conventional and advanced electroanalytical approaches for detecting COVID-19 virus. The popular conventional methods such as polymerase chain reaction (PCR), loop mediated isothermal amplification (LAMP), serology test, and computed tomography (CT) scan with artificial intelligence require specialized equipment, hours of processing, and specially trained staff. Many researchers, on the other hand, focused on the invention and expansion of electrochemical and/or bio sensors to detect SARS-CoV-2, demonstrating that they could show a significant role in COVID-19 disease control. We attempted to meticulously summarize recent advancements, compare conventional and electroanalytical approaches, and ultimately discuss future prospective in the field. We hope that this review will be helpful to researchers who are interested in this interdisciplinary field and desire to develop more innovative virus detection methods.

Indexed as

COVID-19SARS-CoV-2Artificial IntelligenceHumansNucleic Acid Amplification TechniquesPandemicsSensitivity and SpecificityDetectionElectrochemical biosensorModified electrodePoint of carePolymerase chain reactionSARS-CoV-2

Identifiers

PMID35817176
PMCPMC9270057
OpenAlexW4284963223

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.