Development and application of artificial intelligence-based facial skin image diagnosis system: Changes in facial skin characteristics with ageing in Korean women / Hyeokgon Park in INTERNATIONAL JOURNAL OF COSMETIC SCIENCE, Vol. 46, N° 2 (04/2024)  

[article]  inINTERNATIONAL JOURNAL OF COSMETIC SCIENCE > Vol. 46, N° 2 (04/2024) . - p. 199-208 Titre : Development and application of artificial intelligence-based facial skin image diagnosis system: Changes in facial skin characteristics with ageing in Korean women Type de document : texte imprimé Auteurs : Hyeokgon Park, Auteur ; Sae-ra Park, Auteur ; Sangran Lee, Auteur ; Joongwon Hwang, Auteur ; Myeongryeol Lee, Auteur ; Sue Im Jang, Auteur ; Yuchul Jung, Auteur ; Yeongmin Yeon, Auteur ; Nayoung Kang, Auteur ; Byung-Fhy Suh, Auteur ; Eunjoo Kim, Auteur Année de publication : 2024 Article en page(s) : p. 199-208 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Coréen(ne)s Diagnostic biologique Imagerie (technique) Intelligence artificielle Peau -- analyse Peau féminine Index. décimale : 668.5 Parfums et cosmétiques Résumé : - Objective : To develop and validate an artificial intelligence (AI)-based diagnostic system for analysing facial skin images using expert judgements and explore its feasibility for skin ageing research, specifically by evaluating facial skin changes in Korean women of various ages. - Methods : Our AI-based facial skin diagnosis system (Dr. AMORE®) uses facial images of Korean women to analyse wrinkles, pigmentation, skin pores, and other skin red spots. The system is trained using clinical expert evaluations and deep learning. We assessed the system's precision and sensitivity by analysing the correlation between the diagnoses by the AI system and those of the experts. We used 120 images of Korean women aged 10–60 years to evaluate the changes in various facial skin characteristics with ageing. - Results : The precision and sensitivity of the developed system were excellent (>0.9%), and the diagnosis scores using the detected area and intensity of each item were correlated significantly higher with the visual evaluation results of the clinical experts (>0.8, p < 0.001). We also analysed facial images of Korean women aged 10–60 years to quantify changes in the scores of wrinkles, pigmentation, and skin pores with age. We identified the age group with the most significant changes as 20s to 30s. Analysis of the detailed skin characteristics of each item showed that wrinkles and pigmentation changed significantly in the 20s–30s, and skin pores increased significantly in the 10s–20s. There was no significant correlation with age or change according to the age group for skin red spots. - Conclusion : Developed AI-based facial skin diagnosis system can automatically diagnose skin conditions based on clinical expert judgement using only photographic images and analyse various items in detail, quantitatively, and visually. This AI system can provide new and useful approaches in research areas that require a lot of resources and different characterizations, such as the study of facial skin ageing. Note de contenu : - Collecting facial skin images - Image data preparation for AI training - Designing and training an AI skin diagnosis system - Validation of an AI skin diagnosis system - Evaluation of an AI skin diagnostic system's analysis of changes in skin ageing characteristics - Image and statistical analysis - Table 1 : Detailed diagnostic items of AI skin diagnosis system. - Table 2 : Age distribution of Korean female participants to analyse changes in skin ageing characteristics - Table 3 : Results of clinical expert evaluation of detection visualization images of AI skin diagnosis system - Table 4 : Correlation coefficients and significance probabilities of score results for each skin diagnosis item between the clinical experts and the AI skin diagnosis system - Table 5 : Changes in facial skin diagnostic scores according to age in Korean women, correlation coefficients and probability of significance with age, and probability of significant change from adjacent age groups - Table 6 : Changes in facial skin detailed diagnostic items according to age in Korean women, correlation coefficients and probability of significance with age, and probability of significant change from adjacent age groups DOI : https://doi.org/10.1111/ics.12924 En ligne : https://drive.google.com/file/d/171UsYqi87UzenncJQUsWSAdMU-gNRqTY/view?usp=drive [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=40907 [article]

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