Evidence map›Paper›PMID 33005316›Full record

ArticleJournal of healthcare engineering2020

Theoretical Background to Automated Diagnosing of Oral Leukoplakia: A Preliminary Report.

Kamil Jurczyszyn, Tomasz Gedrange, Marcin Kozakiewicz

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 4 pooled it
1.6field-weighted citation impact, top 17% 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

14 citing papers in PubMed, 4 syntheses or guidelines pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  5. Review
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  12. Use of Artificial Intelligence in the Classification of Elementary Oral Lesions from Clinical Images.International journal of environmental research and public health · 2023
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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.

Kamil JurczyszynDepartment of Oral Surgery, Medical University in Wrocław, Wrocław, Poland.ORCID 0000-0002-0667-7261
Tomasz GedrangeDepartment of Orthodontics, TU Dresden, Dresden, Germany.ORCID 0000-0002-3551-6467
Marcin KozakiewiczDepartment of Maxillofacial Surgery, Faculty of Military Medicine, Medical University of Lodz, Łódź, Poland.
Medical University of Lodz · PLTechnische Universität Dresden · DEWroclaw Medical University · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral leukoplakia represents the most common oral potentially malignant disorder, so early diagnosis of leukoplakia is important. The aim of this study is to propose an effective texture analysis algorithm for oral leukoplakia diagnosis. Thirty-five patients affected by leukoplakia were included in this study. Intraoral photography of normal oral mucosa and leukoplakia were taken and processed for texture analysis. Two features of texture, run length matrix and co-occurrence matrix, were analyzed. Difference was checked by ANOVA. Factor analysis and classification by the artificial neural network were performed. Results revealed easy possible differentiation leukoplakia from normal mucosa (

Indexed as

Pattern Recognition, AutomatedDiagnosis, Computer-AssistedHumansImage Processing, Computer-AssistedLeukoplakia, OralMiddle AgedModels, StatisticalModels, TheoreticalMouth MucosaNeural Networks, ComputerSensitivity and SpecificityUser-Computer InterfaceWavelet Analysis

Identifiers

PMID33005316
PMCPMC7509569
OpenAlexW3084759400

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.