Evidence map›Paper›PMID 28717569›Full record

ArticleBiomedical optics express2017

Histogram analysis for smartphone-based rapid hematocrit determination.

Uddin M Jalal, Sang C Kim, Joon S Shim

Abstract read
In one paragraph

Article in Biomedical optics express, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Back to the "Gold Standard": How Precise is Hematocrit Detection Today?Mediterranean journal of hematology and infectious diseases · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

3 authors.

Uddin M JalalBio IT Convergence Laboratory, Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea.
Sang C KimBio IT Convergence Laboratory, Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea.
Joon S ShimBio IT Convergence Laboratory, Department of Electronic Convergence Engineering, Kwangwoon University, Seoul, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel and rapid analysis technique using histogram has been proposed for the colorimetric quantification of blood hematocrits. A smartphone-based "Histogram" app for the detection of hematocrits has been developed integrating the smartphone embedded camera with a microfluidic chip via a custom-made optical platform. The developed histogram analysis shows its effectiveness in the automatic detection of sample channel including auto-calibration and can analyze the single-channel as well as multi-channel images. Furthermore, the analyzing method is advantageous to the quantification of blood-hematocrit both in the equal and varying optical conditions. The rapid determination of blood hematocrits carries enormous information regarding physiological disorders, and the use of such reproducible, cost-effective, and standard techniques may effectively help with the diagnosis and prevention of a number of human diseases.

Indexed as

(040.1880) Detection(100.2960) Image analysis(110.0110) Imaging systems(170.1610) Clinical applications(170.3880) Medical and biological imaging

Identifiers

PMID28717569
PMCPMC5508830

What OpenQuestion holds

Textmetadata
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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.