Facial adult female acne in China : An analysis based on artificial intelligence over one million

© 2024 The Authors. Skin Research and Technology published by John Wiley & Sons Ltd..

BACKGROUND: To further clarify the acne profile of Chinese adult women, we included 1,156,703 adult women. An artificial intelligence algorithm was used to analyze images taken by high-resolution mobile phones to further explore acne levels in Chinese adult women.

METHOD: In this study, we assessed the severity of acne by evaluating patients' selfies through a smartphone application. Furthermore, we gathered basic user information through a questionnaire, including details such as age, gender, skin sensitivity, and dietary habits.

RESULTS: This study showed a gradual decrease in acne severity from the age of 25 years. A trough was reached between the ages of 40 and 44, followed by a gradual increase in acne severity. In terms of skin problems and acne severity, we have found that oily skin, hypersensitive skin, frequent makeup application and unhealthy dietary habits can affect the severity of acne. For environment and acne severity, we observed that developed city levels, cold seasons and high altitude and strong radiation affect acne severity in adult women. For the results of the AI analyses, the severity of blackheads, pores, dark circles and skin roughness were positively associated with acne severity in adult women.

CONCLUSIONS: AI analysis of high-res phone images in Chinese adult women reveals acne severity trends. Severity decreases after 25, hits a low at 40-44, then gradually rises. Skin type, sensitivity, makeup, diet, urbanization, seasons, altitude, and radiation impact acne. Blackheads, pores, dark circles, and skin roughness are linked to acne severity. These findings inform personalized skincare and public health strategies for adult women.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:30

Enthalten 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) - 30(2024), 4 vom: 13. Apr., Seite e13693

Sprache:

Englisch

Beteiligte Personen:

Li, Tian-Hao [VerfasserIn]
Ma, Xu-Da [VerfasserIn]
Li, Zi-Ming [VerfasserIn]
Yu, Nan-Ze [VerfasserIn]
Song, Jin-Yan [VerfasserIn]
Ma, Zi-Tao [VerfasserIn]
Ying, Han-Ting [VerfasserIn]
Zhou, Beibei [VerfasserIn]
Huang, Jiu-Zuo [VerfasserIn]
Wu, Liang [VerfasserIn]
Long, Xiao [VerfasserIn]

Links:

Volltext

Themen:

Adult female acne
Artificial intelligence
Chinese
Deep learning
Journal Article
Skin aging

Anmerkungen:

Date Completed 05.04.2024

Date Revised 06.04.2024

published: Print

Citation Status MEDLINE

doi:

10.1111/srt.13693

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM370620038