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Abstract Aging clocks have emerged as the primary tools for measuring biological age, providing useful tools for personalized medicine and aging interventions. However, in clinical practice, data for most of the current aging clocks (e.g., omics-based clocks) are not always available as they are too expensive or time-consuming. In contrast, patient medical histories are often readily available through electronic health record (EHR) systems.
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