Evidence map›Paper›PMID 37829105›Full record

ArticlePlastic and reconstructive surgery. Global open2023

A Novel Method to Determine Patient Skin Type: The Skin Analyzer.

Youssef Mohamed, Bilal Koussayer, Ellie M Randolph, William West, Julia A Morris, Nicole K Le, Kristen Whalen, Kristina Gemayel, Mahmood J Al Bayati, Jared Troy and 1 more

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Limitations of ITA for Skin Type Estimation Under Uncontrolled Imaging Conditions.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) · 2026
    Article
  2. 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

11 authors.

Youssef MohamedFrom University of South Florida Health Morsani College of Medicine, Tampa, Fla.
Bilal KoussayerFrom University of South Florida Health Morsani College of Medicine, Tampa, Fla.
Ellie M RandolphFrom University of South Florida Health Morsani College of Medicine, Tampa, Fla.
William WestFrom University of South Florida Health Morsani College of Medicine, Tampa, Fla.
Julia A MorrisFrom University of South Florida Health Morsani College of Medicine, Tampa, Fla.
Nicole K LeDepartment of Plastic Surgery, University of South Florida, Tampa, Fla.
Kristen WhalenDepartment of Plastic Surgery, University of South Florida, Tampa, Fla.
Kristina GemayelDepartment of Plastic Surgery, University of South Florida, Tampa, Fla.
Mahmood J Al BayatiDepartment of Plastic Surgery, University of South Florida, Tampa, Fla.
Jared TroyDepartment of Plastic Surgery, University of South Florida, Tampa, Fla.
Jake LaunDepartment of Plastic Surgery, University of South Florida, Tampa, Fla.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measuring skin color for medical research in an objective and nonbiased manner usually requires expensive equipment such as spectrophotometry and requires the subject to be present in person. We present a novel method to measure skin color from photographs using the Skin Analyzer application as a more effective, accessible, and efficient alternative. A desktop application, the Skin Analyzer, was developed to convert skin samples collected from digital images to the L*a*b color space and uses those values to calculate an individual typology angle that correlates to a Fitzpatrick skin type. To assess accuracy in variable lighting, six known colors representing the six Fitzpatrick skin types were printed and photographed in 15 separate locations within the hospital. To account for user variability in sample selection, interrater reliability was calculated with data generated by 13 untrained users testing the app on six subjects. The accuracy of measuring known values, which is the classification accuracy, was calculated to be 80%. Krippendorff alpha test was used to evaluate interrater reliability. The obtained alpha of 0.84 indicates a high interrater reliability. The high accuracy and reliability make the Skin Analyzer a suitable method of objectively determining Fitzpatrick skin type from images. The app may be used to investigate the effects of skin tone in various areas of interest, especially in retrospective studies where skin colorimeters cannot be used.

Identifiers

PMID37829105
PMCPMC10566767

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LicenceCC BY-NC-ND
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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.