Unlocking secrets of aging: ENABL age offers detailed, individualized aging profiles using cutting-edge AI techniques

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Unlocking secrets of aging: ENABL age offers detailed, individualized aging profiles using cutting-edge AI techniques
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Combining machine learning with explainable artificial intelligence (XAI) to predict biological age with personalized explanations.

By Pooja Toshniwal PahariaNov 9 2023Reviewed by Lily Ramsey, LLM In a recent study published in The Lancet Healthy Longevity, researchers introduced a computational ExplaiNAble BioLogical Age estimation framework combining machine learning with explainable artificial intelligence to predict biological age with personalized explanations.

Studies have concentrated on first-generation biological age clocks aimed at predicting chronological age. These clocks have fewer connections with mortality risk than second-generation clocks, and their relationships with other aging outcomes are varied. Enhanced XAI techniques were used to derive the Shapley additive explanations values and determine the extent to which the input features contributed to ENABL Age estimation.

Features missing in most samples, highly correlated features, and individuals who died due to external reasons were excluded. ENABL Age attained high mortality estimation power, as indicated by the area under the receiver operating characteristic curve values of 0.8 for five- and ten-year mortality among UKBB participants and 0.9 for the corresponding mortality estimations among NHANES participants.

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