“He not busy being born is busy dying,” sang Bob Dylan, and of course he’s right. We’re all ticking time bombs in our way.

We think that, by and large, we pass on in order of age, but that’s just one metric, and it’s a pretty coarse-grained one. There are lots of other predictors of longevity, and each has its own health and “age”—its own clock, if you will.

Young.AI is a new project currently in beta testing that uses A.I. to track the “age” of our systems in order to derive a more meaningful prediction of our biological age, and thus our lifespan.

It seeks to identify the weakest clocks as the ones most likely to become life-threatening.  Young.AI is a project of Insilico Medicine, whose mission is the use of “Artificial Intelligence For Drug Discovery, Biomarker Development & Aging Research.” It follows a deep-learning analysis by Insilico of blood tests from 130,000 South Koreans, Canadians, and Eastern Europeans. Scientists from Johns Hopkins, University of Oxford, and other research institutions participated in the study.

This was apparently the largest such analysis ever performed in the longevity field, and it produced a model using “several deep learning-based predictors of biological age trained upon population-specific blood biochemistry and haematological cell count datasets.” It was published in the Journal of Gerontology.  Polina Mamoshina, a senior research scientist at Insilico Medicine, says that “today, thanks to A.I. and the incredibly fast computational power of our deep learning neural networks, we can discover patterns and formulas in a huge pool of blood work that could not be discovered just a few years ago.” The project looked at 21 commonly measured blood parameters such as cholesterol, inflammation markers (CRP), hemoglobin count, and albumin levels, along with 17 other chemical indicators. Read more from bigthink.com…

thumbnail courtesy of bigthink.com