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.

Frederic FlamentRuowei JiangJeff HoughtonYuze ZhangCamille KroelyNina G JablonskiAurelie JeanJeffrey ClarkeJason SteegCassidy SehgalJames McParlandCaroline DelaunayThierry Passeron

Published in: Journal of the European Academy of Dermatology and Venereology : JEADV (2022)

The 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.

Keyphrases

deep learning
polycystic ovary syndrome
soft tissue
machine learning
artificial intelligence
pregnancy outcomes
convolutional neural network
minimally invasive
pregnant women
high resolution
neural network
adipose tissue
mass spectrometry