Looking and feeling younger is a goal for many not to mention a massive industry in selling youth through all sorts of means. However, understanding the exact factors that influence the aging process is still a really untapped research areas.
Identifying and understanding these factors offers valuable insight into how to minimize them and in turn slow or halt aging. Now a skincare company and a medical research company have teamed up to develop a simple and accurate predictor of chronological age called the PhotoAgeClock.
Predicting age can unlock preventative measures
Haute.ai and Incscillio Medicine developed the program together and have recently published their results online. PhotoAgeClock uses deep learning algorithms to understand the visual biomarkers of a person's age.
Its creators hope this is the first in many steps towards an AI-powered skin and healthcare future. "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.
Understanding the many biological processes in skin using AI may lead to the many breakthroughs down the road," said Anastasia Georgievskaya, CEO of Haut AI, an Estonia-based artificial intelligence company.
The area around the eye is the biggest age marker
The research found that the area of skin around the eye is the best biomarker for determining age. The PhotoAgeClock uses AI to be able to predict a persons age with predict age with 2.3 years Mean Absolute Error (MAE).
The study used 8,414 high-resolution images of left and right eye corner photos. It was found that only a small facial region was needed to complete high-quality age estimations.
The area around the eye and eyelid had the most significant impact on age prediction. The creators of the system are confident that they can accurately predict a persons age using anonymized photographs of the eye area.
This information can then be used to develop personalized medical interventions and skin treatments for aging. The system can also be used for long-term research into evaluating the impact that lifestyle, medical, and cosmetic interventions have on aging.
"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.
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," said Alex Zhavoronkov," PhD, CEO of Insilico Medicine.
The research has been published in a paper titled, "PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging," published in the journal Aging.