Evidence map›Paper›PMID 40193151›Full record

ArticleJournal of cosmetic dermatology2025

An Automatic AI-Based Algorithm That Grades the Scalp Surface Exfoliating Process From Video Imaging. Application to Dandruff Severity and Its Validation on Subjects of Different Ages and Ethnicities.

Frederic Flament, Ava Mondji, Chengda Ye, Zeneng Sun, Panagiotis-Alexandros Bokaris, Benjamin Askenazi, Emmanuel Malherbe, Romain Roncin, Aldina Suwanto, Adrien Chretien and 5 more

Abstract readValidation Study
In one paragraph

Article in Journal of cosmetic dermatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

15 authors.

Frederic FlamentL'Oréal Research and Innovation, Clichy, France.ORCID https://orcid.org/0000-0003-1128-9535
Ava MondjiL'Oréal Research and Innovation, Clichy, France.
Chengda YeL'Oréal Research and Innovation, Shanghai, China.
Zeneng SunL'Oréal Research and Innovation, Shanghai, China.
Panagiotis-Alexandros BokarisL'Oréal Research and Innovation, Clichy, France.
Benjamin AskenaziL'Oréal Research and Innovation, Clichy, France.
Emmanuel MalherbeL'Oréal Research and Innovation, Shanghai, China.ORCID https://orcid.org/0009-0006-0898-6873
Romain RoncinL'Oréal Research and Innovation, Clichy, France.
Aldina SuwantoL'Oréal Research and Innovation, Clichy, France.
Adrien ChretienL'Oréal Research and Innovation, Clichy, France.
Maxime De BoniL'Oréal Research and Innovation, Shanghai, China.
Angeline YoungGleneagles Medical Centre, Singapore.
Bianca Maria PiracciniDermatology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Victoria BarbosaSection of Dermatology, University of Chicago Medicine, Chicago, Illinois, USA.
Guive BaloochL'Oréal Research and Innovation, Clichy, France.

Funding

L'Oréal Research & Innovation
6 · The paper itself

Abstract

objectivesTo evaluate the technical assets of a new imaging device that, wifi linked to a AI based algorithm, automatically grades in vivo the exfoliating process of the skin, taking dandruff as model. MATERIAL AND

methodsThe hand portable device comprises a camera that possibly uses three illuminating conditions (white LED diffused lamp, cross-polarized white light and UVA rays). The learning phase of the algorithm was built on 3600 images of the vertex area of 234 subjects of different ages and three ethnicities with and without dandruff. This learning phase allowed 15 experts and dermatologists to score regarding a 6-point atlas of dandruff severities, taken as reference. In a second validation phase, 460 images from 192 subjects of different ages and ethnic background/phototypes, were automatically analyzed by the AI based device, allowing to calculate the correlation between expert's assessments and the gradings provided by the device, and, as second indicator, to compute the Mean Average Error (MAE) between both variables.

resultsThe values were found significantly correlated (r

conclusionThis new imaging device coupled with AI-based analysis allows a valid, rapid, and easy determination of the scalp exfoliating process and may represent a complementary help in the diagnosis of dermatologists in some other scalp disorders. Its versatility, easy handling, and immediate AI-based analysis suggest that it may be applied to other cosmetic areas (skincare, makeup, haircare, etc.).

Indexed as

AlgorithmsArtificial IntelligenceScalpAdolescentAdultAgedAge FactorsFemaleHumansMaleMiddle AgedPhotographySeverity of Illness IndexVideo RecordingYoung Adultageclinical imagingdandruffethnic groupsexfoliationscalp

Identifiers

PMID40193151
PMCPMC11975186

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.