Observational studyJournal of the European Academy of Dermatology and Venereology : JEADV2023
Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.
Observational study in Journal of the European Academy of Dermatology and Venereology : JEADV, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cosmetogenomics unveiled: a systematic review of AI, genomics, and the future of personalized skincare.Frontiers in artificial intelligence · 2025Pooled it
- From skin aging biomarkers to precision esthetic longevity: a translational diagnostic framework.Frontiers in medicine · 2026Article
- Unlocking Longevity in Aesthetic Dermatology: Epigenetics, Aging, and Personalized Care.International journal of dermatology · 2025Review
- Clinical Age-reversal Quantification of a Facial Skincare Regimen with Sirtuin-targeting Ingredients in a Multiethnic Population.The Journal of clinical and aesthetic dermatology · 2025Article
- Development of a Novel Facial Age Assessment Model in a Multiethnic Population for Evaluation of Topical Anti-Aging Products.The Journal of clinical and aesthetic dermatology · 2025Article
- Transforming Aesthetic Dermatology: The Role of Artificial Intelligence in Skin Health.Dermatology and therapy · 2025Review
- Advances in Longevity: The Intersection of Regenerative Medicine and Cosmetic Dermatology.Journal of cosmetic dermatology · 2025Review
- 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.Journal of cosmetic dermatology · 2025Article
- Predictive Biomarkers: A New Frontier in Bespoke Aesthetic Dermatology.Aesthetic surgery journal. Open forum · 2025Article
- Bridging clinic to home: domestic devices in dermatological diagnostics and treatments.Frontiers in digital health · 2025Article
- Artificial intelligence in cosmetic dermatology.Journal of cosmetic dermatology · 2024Review
- The relevance and accuracy of an AI algorithm-based descriptor on 23 facial attributes in a diverse female US population.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) · 2024Article
- Differences in the annotation between facial images and videos for training an artificial intelligence for skin type determination.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) · 2024Article
- 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) · 2023Article
- Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.Journal of the European Academy of Dermatology and Venereology : JEADV · 2023Observational
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundReal-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes.
objectivesTo explore the relevance and accuracy of an automated, algorithm-based analysis of facial signs in representative women of different ancestries, ages and phototypes, living in the same country.
methodsIn a cross-sectional study of selfie images of 1041 US women, algorithm-based analyses of seven facial signs were automatically graded by an AI-based algorithm and by 50 US dermatologists of various profiles (age, gender, ancestry, geographical location). For automated analysis and dermatologist assessment, the same referential skin atlas was used to standardize the grading scales. The average values and their variability were compared with respect to age, ancestry and phototype.
resultsFor five signs, the grading obtained by the automated system were strongly correlated with dermatologists' assessments (r ≥ 0.75); cheek skin pores were moderately correlated (r = 0.63) and pigmentation signs, especially for the darkest skin tones, were weakly correlated (r = 0.40) to the dermatologist assessments. Age and ancestry had no effect on the correlations. In many cases, the automated system performed better than the dermatologist-assessed clinical grading due to 0.3-0.5 grading unit differences among the dermatologist panel that were not related to any individual characteristic (e.g. gender, age, ancestry, location). The use of phototypes, as discontinuous categorical variables, is likely a limiting factor in the assessments of grading, whether obtained by automated analysis or clinical assessment of the images.
conclusionsThe AI-based automatic procedure is accurate and clinically relevant for analysing facial signs in a diverse and inclusive population of US women, as confirmed by a diverse panel of dermatologists, although skin tone requires further improvement.
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Registered trials
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.