Evidence map›Paper›PMID 26517973›Full record

ArticleSkin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)2016

Objective measurement of erythema in psoriasis using digital color photography with color calibration.

A Raina, R Hennessy, M Rains, J Allred, J M Hirshburg, D G Diven, M K Markey

Open access · bronzeAbstract read
In one paragraph

Article in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 29 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

A RainaBiomedical Engineering Department, The University of Texas at Austin, Austin, TX, USA.
R HennessyBiomedical Engineering Department, The University of Texas at Austin, Austin, TX, USA.
M RainsDepartment of Dermatology, The University of Texas at Austin, Dell Medical School, Austin, TX, USA.
J AllredDepartment of Dermatology, The University of Texas at Austin, Dell Medical School, Austin, TX, USA.
J M HirshburgDepartment of Dermatology, The University of Texas at Austin, Dell Medical School, Austin, TX, USA.
D G DivenDepartment of Dermatology, The University of Texas at Austin, Dell Medical School, Austin, TX, USA.
M K MarkeyBiomedical Engineering Department, The University of Texas at Austin, Austin, TX, USA.
The University of Texas at Austin · USThe University of Texas MD Anderson Cancer Center · US

Funding

Comprehensive Training Program in Imaging Science and InformaticsT32EB007507 · NIBIB · UNIVERSITY OF TEXAS AT AUSTIN · PI MARKEY, MIA K, RYLANDER, HENRY GRADY · 2009 to 2024
$2.7M
NIBIB NIH HHS T32 EB007507
6 · The paper itself

Abstract

backgroundTraditional metrics for evaluating the severity of psoriasis are subjective, which complicates efforts to measure effective treatments in clinical trials.

methodsWe collected images of psoriasis plaques and calibrated the coloration of the images according to an included color card. Features were extracted from the images and used to train a linear discriminant analysis classifier with cross-validation to automatically classify the degree of erythema. The results were tested against numerical scores obtained by a panel of dermatologists using a standard rating system.

resultsQuantitative measures of erythema based on the digital color images showed good agreement with subjective assessment of erythema severity (κ = 0.4203). The color calibration process improved the agreement from κ = 0.2364 to κ = 0.4203.

conclusionWe propose a method for the objective measurement of the psoriasis severity parameter of erythema and show that the calibration process improved the results.

Indexed as

AdultCalibrationColorColorimetryErythemaFemaleHumansImage EnhancementImage Interpretation, Computer-AssistedMachine LearningMaleMiddle AgedPattern Recognition, AutomatedPhotographyPsoriasisReproducibility of Resultscolor calibrationimage processingmachine learningpsoriasis

Identifiers

PMID26517973
PMCPMC4851905
OpenAlexW2208469235

What OpenQuestion holds

Textmetadata
LicenceTDM
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.