Abstract
Aging biomarkers are the qualitative and quantitative indicators of the aging processes of the human body. Estimation of biological age is important for assessing the physiological state of an organism. The advent of machine learning lead to the development of the many age predictors commonly referred to as the “aging clocks” varying in biological relevance, ease of use, cost, actionability, interpretability, and applications. Here we present and investigate a novel non-invasive class of visual photographic biomarkers of aging. We developed a simple and accurate predictor of chronological age using just the anonymized images of eye corners called the PhotoAgeClock. Deep neural networks were trained on 8414 anonymized high-resolution images of eye corners labeled with the correct chronological age. For people within the age range of 20 to 80 in a specific population, the model was able to achieve a mean absolute error of 2.3 years and 95% Pearson and Spearman correlation.
Highlights
One of the critical challenges in aging and longevity research and healthcare in general is the development of widely-available and reliable biomarkers of aging
The results clearly indicate that high-resolution information about eye corner wrinkles can be utilized for accurate chronological age estimation
The experiment implicates that the wrinkles in the eye region contained the most important features for age prediction suggesting that these areas may be used for development of candidate photographic aging biomarkers
Summary
One of the critical challenges in aging and longevity research and healthcare in general is the development of widely-available and reliable biomarkers of aging. Individuals can be of the same chronological age and have different biological ages. Biological age reflects functional capability and physiological status, whereas perceived age reflects the age other people guess a person to be [1]. Chronological age predictors can be used to identify the divergence between estimated biological or perceived age and true chronological age among people with accelerated or delayed aging [1]. It is important to develop non-invasive photographic biomarkers, since they are capable of providing valuable insights about the condition of the human www.aging‐us.com body. Highly-accurate predictors of chronological age can be used to evaluate the various lifestyle, medical, and cosmetic interventions
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