AI RESEARCH
Trust Aware Federated Learning for Secure Bone Healing Stage Interpretation in e-Health
arXiv CS.LG
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ArXi:2603.06646v1 Announce Type: new This paper presents a trust aware federated learning (FL) framework for interpreting bone healing stages using spectral features derived from frequency response data. The primary objective is to address the challenge posed by either unreliable or adversarial participants in distributed medical sensing environments. The framework employs a multi-layer perceptron model trained across simulated clients using the Flower FL framework.