• Mashup Score: 2

    Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep learning (DL). However, building powerful and robust DL models requires training with large multi-party datasets. While multiple stakeholders have provided publicly available datasets, the ways in which these data are labeled vary widely. For Instance, an institution might provide a dataset of chest…

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    • Collaborative training of medical artificial intelligence models with non-uniform labels https://t.co/I5DQh9ZJcT #AI #FederatedLearning #radiology #digitalhealth

  • Mashup Score: 0

    To create real-time, privacy-preserving AI in medicine, applications require a new decentralized computing infrastructure

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    • In post 5 of 8, Dr. @timothychou, explores how Apple uses #federatedlearning to improve their #AItechnologies. Learn more about decentralized systems in post 4: https://t.co/q6R7LyaaYK Read the full article> https://t.co/X1n0S6g7ij #aimed #healthcare