Evidence map›Paper›PMID 28350891›Full record

ArticlePloS one2017

An on-chip instrument for white blood cells classification based on a lens-less shadow imaging technique.

Yuan Fang, Ningmei Yu, Runlong Wang, Dong Su

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Yuan FangSchool of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.ORCID http://orcid.org/0000-0002-5138-3895
Ningmei YuSchool of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.ORCID http://orcid.org/0000-0002-4219-8364
Runlong WangSchool of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.
Dong SuSchool of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Routine blood tests provide important basic information for disease diagnoses. The proportions of three subtypes of white blood cells (WBCs), which are neutrophils, monocytes, lymphocytes, is key information for disease diagnosis. However, current instruments for routine blood tests, such as blood cell analyzers, flow cytometers, and optical microscopes, are cumbersome, time consuming and expensive. To make a smaller, automatic low-cost blood cell analyzer, much research has focused on a technique called lens-less shadow imaging, which can obtain microscopic images of cells in a lens-less system. Nevertheless, the efficiency of this imaging system is not satisfactory because of two problems: low resolution and imaging diffraction phenomena. In this paper, a novel method of classifying cells with the shadow imaging technique was proposed. It could be used for the classification of the three subtypes of WBCs, and the correlation of the results of classification between the proposed system and the reference system (BC-5180, Mindray) was 0.93. However, the instrument was only 10 × 10 × 10 cm, and the cost was less than $100. Depending on the lens-free shadow imaging technology, the main hardware could be integrated on a chip scale and could be called an on-chip instrument.

Indexed as

Lab-On-A-Chip DevicesAlgorithmsBiosensing TechniquesCost-Benefit AnalysisHumansLeukocyte CountLeukocytesMetalsOptical ImagingOxidesReproducibility of ResultsSemiconductorsMetalsOxides

Identifiers

PMID28350891
PMCPMC5370127

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.