Federated learning for privacy-preserving medical data sharing in drug development

HIGHLIGHTS

• What: This study explores the potential of Federated Learning (FL) to facilitate the sharing and collaboration of medical data in drug development under the premise of privacy protection. The authors implemented and evaluated a federal learning system for drug development data sharing.
• Who: Mingxuan Yang et al. from the Brown University, RI, USA have published the article: Federated Learning for Privacy-Preserving Medical Data Sharing in Drug Development, in the : Proceedings of the 5th International Conference on Signal Processing and Machine Learning
• Future: Future research could further optimize communication efficiency model aggregation strategies . . .
  

   

  

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