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Using AI to estimate biological age with deep aging clocks
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Abstract
Several aging clocks have been developed to measure biological aging and assess the efficacy of longevity interventions.
- Biological age is closely associated with health outcomes and time to mortality.
- Traditional aging clocks assume biological changes occur linearly, which may not reflect reality.
- Deep Aging Clocks have been created to capture non-linear age-related changes more effectively.
- Current deep aging clocks include methods based on epigenetics, transcriptomics, metabolomics, microbiome, and imaging.
- Advancements in artificial intelligence have improved the prediction accuracy of biological aging.
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