Evidence map›Paper›PMID 35942252›Full record

ArticleAdvanced materials technologies2022

An Internet-of-Disease System for COVID-19 Testing Using Saliva by an AI-Controlled Microfluidic ELISA Device.

Nabil Hossain Bhuiyan, Md Jalal Uddin, Joowon Lee, Jun Hyeok Hong, Joon Sub Shim

Abstract read
In one paragraph

Article in Advanced materials technologies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. 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

5 authors.

Nabil Hossain BhuiyanBio-IT Convergence Laboratory Department of Electronic Convergence Engineering KwangWoon University Seoul 01897 Republic of Korea.
Md Jalal UddinBio-IT Convergence Laboratory Department of Electronic Convergence Engineering KwangWoon University Seoul 01897 Republic of Korea.
Joowon LeeBio-IT Convergence Laboratory Department of Electronic Convergence Engineering KwangWoon University Seoul 01897 Republic of Korea.
Jun Hyeok HongBio-IT Convergence Laboratory Department of Electronic Convergence Engineering KwangWoon University Seoul 01897 Republic of Korea.
Joon Sub ShimBio-IT Convergence Laboratory Department of Electronic Convergence Engineering KwangWoon University Seoul 01897 Republic of Korea.ORCID https://orcid.org/0000-0003-4749-5648

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Throughout coronavirus disease (COVID-19) outbreaks, the centers for disease control and prevention (CDCP) of a country require monitoring of particular territories to provide public health guidance. In this work, the Internet of Diseases (IoD) is suggested for continuous real-time monitoring of infectious diseases for public health. Because converging information and communication technologies (ICTs) with point-of-care (POC) devices to enable the IoD for continuous real-time health monitoring and processing of clinical records are crucial, an IoD platform associating a lab-on-a-chip (LOC) device to diagnose severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) from oropharyngeal saliva samples have been developed and uploaded the resulted diagnostic data into a cloud-based system to be connected with CDCP. Moreover, a choropleth IoD map to visualize provincial infection rate is proposed along with the IoD platform. The developed platform is applied for the quantification of SARS-CoV-2 N-protein antigen with a LOD as low as 0.013 ng mL

Indexed as

COVID‐19internet‐of‐diseaselab‐on‐a‐chipN‐proteinpoint‐of‐care

Identifiers

PMID35942252
PMCPMC9349700

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.