Modernizing Our Health Data Ecosystem Using Wastewater, Wearables, And Web Data
Abstract
Building a federated data network for global disease surveillance balances privacy with situational awareness and could foster access to analytics and peer learning groups, inform the public about disease risks, and provide early warnings to rural or impoverished areas that lack resources for surveillance.
Read the paper
Related studies
- Active Learning during Federated Learning for Object Detection
- Fairness-aware federated learning
- Decentralized Federated Learning
- Building a Personally Identifiable Information Recognizer in a Privacy Preserved Manner Using Automated Annotation and Federated Learning
- Preservation of Patient Level Privacy: Federated Classification and Calibration Models
- Efficient explainable federated learning
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.