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A Trust-Network-Based Federated Learning Framework for Multi-Center Aging Clock Prediction

arXiv · AI, language, vision and robotics · article · Sep 9, 2026 · UTC

Aging clocks quantify biological aging and help characterize individual health status. What protein interactions are important for accurate aging clocks, and are they zeroth-order or higher-order? Addressing these questions requires learning from large molecular datasets distributed across medical centers, where privacy constraints prevent centralized data sharing. Federated learning offers a natural solution but faces four challenges in this setting: limited local sample sizes, sparse and directional inter-center trust, the need to retain discriminative age prediction while supporting interpr

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