Evidence map›Paper›PMID 28646862›Full record

ArticleBiomedical engineering online2017

A clinical utility assessment of the automatic measurement method of the quality of Meibomian glands.

Robert Koprowski, Lei Tian, Paweł Olczyk

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 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
2.7field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 35 citations in OpenAlex.

  1. Review
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  6. Meibomian glands visibility assessment through a new quantitative method.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2021
    Article
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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 at 3 institutions in 2 countries.

Robert KoprowskiDepartment of Biomedical Computer Systems, Faculty of Computer Science and Materials Science, Institute of Computer Science, University of Silesia, ul. Będzińska 39, 41-200, Sosnowiec, Poland.
Lei TianBeijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China. tianlei0131@163.com.
Paweł OlczykDepartment of Community Pharmacy, School of Pharmacy with the Division of Laboratory Medicine in Sosnowiec, Medical University of Silesia in Katowice, Katowice, Poland.
Capital Medical University · CNInstitute of Computer Science · PLMedical University of Silesia · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeibomian gland dysfunction (MGD) is one of the most common diseases observed in clinics and is the leading cause of evaporative dry eye. Today, diagnostics of MGD is not fully automatic yet and is based on a qualitative assessment made by an ophthalmologist. Therefore, an automatic analysis method was developed to assess MGD quantiatively. MATERIALS: The analysis made use of 228 images of 57 patients recorded by OCULUS Keratograph

methodsThe presented method of analysis is a new, developed method enabling an automatic, reproducible and quantitative assessment of Meibomian glands. The analysis relates to employing the methods of analysis and image processing. The analysis was conducted in the Matlab environment Version 7.11.0.584, R2010b, Java VM Version: Java 1.6.0_17-b04 with Sun Microsystems Inc. with toolboxes: Statistical, Signal Processing and Image Processing.

resultsThe presented, new method of analysis of Meibomian glands is fully automatic, does not require operator's intervention, allows obtaining reproducible results and enables a quantitative assessment of Meibomian glands. Compared to the other known methods, particularly with the method described in literature it allows obtaining better sensitivity (98%) and specificity (100%) results by 2%.

Indexed as

Image Processing, Computer-AssistedAutomationCase-Control StudiesEyelid DiseasesFemaleHumansMaleMeibomian GlandsSignal Processing, Computer-AssistedAutomatic analysisBiomedicalDry eyeImage processingMeibomian gland dysfuction

Identifiers

PMID28646862
PMCPMC5483265
OpenAlexW2641826534

What OpenQuestion holds

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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.