Haute and Incscillio Medicine have recently developed a program, PhotoAgeClock, which uses deep learning algorithms to understand the visual biomarkers of a person’s age. The creators are hoping that this will be the first in many steps towards an AI-powered skin and healthcare future. Anastasia Georgievskaya, CEO of Haut AI, said, “We are very happy to collaborate with one of the most innovative, global, and ethical consumer companies committed to benefit consumers around the world on this important artificial intelligence project. The future of consumer business is in personalization and I hope that this study will lay the foundation for AI-powered consumer skincare and healthcare. Skin is our largest and one of the most important organs.”
He further added, “Understanding the many biological processes in skin using AI may lead to the many breakthroughs down the road.” The research found that the area of skin around the eyes is the best biomarker to determine the age of a person. The PhotoAgeClock uses AI to predict a person’s age and predict age with 2 to 3 years Mean Absolute Error (MAE). The study used 8414 high-resolution images of left and right eye corner photos. Only a small facial region was needed to complete the high-quality age estimations. The area around the eye and eyelid have the most significant impact on the age prediction. The system can accurately predict a person’s age using anonymous photographs of the eye area.
The information obtained is then used to develop personalized medical interventions and skin treatments for aging. The system is also used for long-term research to evaluate the effects of a person’s lifestyle, medical, and cosmetics on aging. Alex Zhavoronkov, a PhD, and CEO of Insilico Medicine, said, “Deep neural networks are often perceived as the black boxes; however, this is a common misconception. Aging research helps make DNNs more interpretable. This study shows what area of the face is most important for age estimation but when you do it on other data types like gene or protein expression, it is possible to see what genes are more important and construct the causal networks.”
He further added, “I personally believe that the AI aging clocks are among the most important breakthroughs in longevity biotechnology and we will see the many advances resulting from similar studies. As for this study, you may want to take care of the eye corners if you want to look younger to some of the age predictors.” The research has been published with the title ‘PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging.’