Enhanced Early Disease Detection via Nanowire-Based Microfluidic Biosensors and Federated Learning

**Abstract:** This paper proposes a novel system for enhanced early disease detection combining nanowire-based microfluidic biosensors with federated learning (FL) to address limitations of traditional diagnostic methods and data privacy concerns. Nanowire sensor arrays fabricated with precisely controlled doping gradients provide unprecedented sensitivity to subtle biomarker changes, while FL allows the decentralized training of diagnostic models across multiple clinical sites without sharing raw patient data. A tailored hyper-scoring mechanism further refines model confidence and minimizes false positives. This approach holds the potential to significantly improve early disease detection rates, enabling more effective interventions and impacting patient outcomes across diverse populations.