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Federated AI, Current State, and Future Potential.

Phoebe ClarkEric K OermannDinah ChenLama A Al-Aswad
Published in: Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) (2023)
Artificial intelligence and machine learning applications are becoming increasingly popular in health care and medical devices. The development of accurate machine learning algorithms requires large quantities of good and diverse data. This poses a challenge in health care because of the sensitive nature of sharing patient data. Decentralized algorithms through federated learning avoid data aggregation. In this paper we give an overview of federated learning, current examples in healthcare and ophthalmology, challenges, and next steps.
Keyphrases
  • machine learning
  • artificial intelligence
  • big data
  • healthcare
  • deep learning
  • electronic health record
  • case report
  • current status
  • health information
  • mass spectrometry
  • data analysis