Scientists publish the first human psychological aging clock using artificial intelligence

[erek]

"PsychoAge and SubjAge: development of deep markers of psychological and subjective age using artificial intelligence.​

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Aging clocks that accurately predict human age based on various biodata types are among the most important recent advances in biogerontology. Since 2016 multiple deep learning solutions have been created to interpret facial photos, omics data, and clinical blood parameters in the context of aging. Some of them have been patented to be used in commercial settings. However, psychological changes occurring throughout the human lifespan have been overlooked in the field of “deep aging clocks”.
In this paper, we present two deep learning predictors trained on social and behavioral data from Midlife in the United States (MIDUS) study: (a) PsychoAge, which predicts chronological age, and (b) SubjAge, which describes personal aging rate perception. Using 50 distinct features from the MIDUS dataset these models have achieved a mean absolute error of 6.7 years for chronological age and 7.3 years for subjective age. We also show that both PsychoAge and SubjAge are predictive of all-cause mortality risk, with SubjAge being a more significant risk factor.
Both clocks contain actionable features that can be modified using social and behavioral interventions, which enables a variety of aging-related psychology experiment designs. The features used in these clocks are interpretable by human experts and may prove to be useful in shifting personal perception of aging towards a mindset that promotes productive and healthy behaviors.

Aging in humans is a process that affects all levels of biological organization: from molecular to systemic. Lower level facets of aging have been studied the most extensively, which has led to the identification of numerous molecular to cellular “hallmarks of aging”: telomere attrition, genome instability, epigenetic dysregulation, shifts in gene expression patterns and metabolic profiles [1–3]. Longitudinal studies of these processes have produced multiple “aging biomarkers”, which are the most convenient and reliable features to determine the extent of the aging-related changes in the human body. The degree of such changes is usually expressed as “biological age” — a numeric value describing how typical the observed biomarker configuration is for healthy chronological age peers within a population [4]. Higher biological age values indicate the higher intensity of aging-related detrimental processes, while lower biological age — higher resilience to them. Traditionally, biological age metrics are designed to resemble the chronological age distribution within a cohort of healthy individuals, while being more predictive of a person’s health status than chronological age itself [5]."

https://eurekalert.org/pub_releases/2020-12/dll-spt121520.php

 

[clockdogg]

Fascinating. As I've learned over my [H]ard years... Aging is inevitable, but immaturity lasts forever.

 

[Krenum]

Speaking of time and age, I recently read an article about how time seems to go faster as you age. It has to do with rapid eye movement and your brains ability to process images. Very interesting.