Artificial Neural Networks guess patient’s age with surprising accuracy

IMAGE: This is the Aging.AI logo. view more Credit: Insilico Medicine Summary: Deep learning methods are propagating into biomarker discovery and aging research This system may provide insight into the biological age of the person if the person “looks” older or younger to Aging.AI then his/her chronological age- Inspired by Microsoft’s How-Old.net, Insilico Medicine scientists created Aging.AI, which guesses patient’s age using basic and inexpensive blood tests An Ensemble of Deep Neural Networks achieved 83.5% accuracy within a 10-year frame (r = 0.91 with R2 = 0.82 and MAE = 5.55 years) when guessing chronological age outperforming many other available markers of aging Insilico Medicine’s Pharma.AI division is soon to publish a range of drug and nutraceutical predictions called geroprotectors, where organismal and tissue-specific efficacy is predicted using a system trained…


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