Evidence map›Paper›PMID 37113093›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)2023

Objective and automatic grading system of facial signs from smartphones' pictures in South African men: Validation versus dermatologists and characterization of changes with age.

Frederic Flament, Ruowei Jiang, Jeff Houghton, Matthieu Cassier, David Amar, Caroline Delaunay, Guive Balooch, Elisabeth Bouhadana, Parham Aarabi, Thierry Passeron

Open access · hybridAbstract 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), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Artificial dermatitis versus artificial intelligence: Detecting etiology with Google Lens.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) · 2024
    Article
  3. Facial adult female acne in China: An analysis based on artificial intelligence over one million.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) · 2024
    Article
  4. Objective and automatic grading system of facial signs from smartphones' pictures in South African men: Validation versus dermatologists and characterization of changes with age.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) · 2023
    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

10 authors at 2 institutions in 1 country.

Frederic FlamentL'Oréal Research and Innovation, Clichy, France.
Ruowei JiangModiFace - A L'Oréal Group Company, Toronto, Ontario, Canada.
Jeff HoughtonModiFace - A L'Oréal Group Company, Toronto, Ontario, Canada.
Matthieu CassierL'Oréal Research and Innovation, Clichy, France.
David AmarL'Oréal Research and Innovation, Clichy, France.
Caroline DelaunayL'Oréal Research and Innovation, Clichy, France.
Guive BaloochL'Oréal Research and Innovation, Clichy, France.
Elisabeth BouhadanaL'Oréal, Clichy, France.
Parham AarabiModiFace - A L'Oréal Group Company, Toronto, Ontario, Canada.
Thierry PasseronDepartment of Dermatology, Université Côte d'Azur, CHU Nice, Nice, France.
L'Oréal (France) · FRCentre Hospitalier Universitaire de Nice · FR

Funding

L'Oréal Research & Innovation
6 · The paper itself

Abstract

objectiveTo evaluate the capacity of the automatic detection system to accurately grade, from selfie pictures, the severity of eight facial signs in South African men.

methodsSelfie pictures (obtained from frontal and back cameras) of 281 South African men differently aged (20-70 years) were obtained and analyzed by an automatic artificial intelligence (AI)-based automatic grading system. Data were compared with the clinical gradings made by experts and dermatologists.

resultsIn all facial signs, both series of gradings were found highly correlated with, however, different coefficients (0.59-0.95), those of marionette lines and cheek pores being of lower values. No differences were observed between data obtained by frontal and back cameras. With age, in most cases, gradings show up to the 50-59 year age-class, linear-like changes. When compared to men of other ancestries, South African men present lower wrinkles/texture, pigmentation, and ptosis/sagging scores till 50-59 years, albeit not much different in the cheek pores sign. The early onset (mean age) of visibility of wrinkles/texture for South African men were (i.e., reaching grade >1) 39 and 45 years for ptosis/sagging.

conclusionThis study completes and enlarges the previous works conducted on men of other ancestries by showing some South African specificities and slight differences with men of comparable phototypes (Afro American).

Indexed as

Skin AgingSmartphoneAdultArtificial IntelligenceDermatologistsFaceHumansMaleMiddle AgedSouth Africaartificial intelligenceclinical signsdiversitymennomad evaluation

Identifiers

PMID37113093
PMCPMC10234158
OpenAlexW4367320545

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.