Extremely Randomized Trees With Privacy Preservation for Distributed Structured Health Data

Extremely Randomized Trees With Privacy Preservation for Distributed Structured Health Data

Artificial intelligence and machine learning have recently attracted considerable attention in the healthcare domain. The data used by machine learning algorithms in healthcare applications is often distributed over multiple sources, for instance, hospitals or patients’ personal devices....

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Bibliographic Details
Main Authors: Amin Aminifar, Matin Shokri, Fazle Rabbi, Violet Ka I. Pun, Yngve Lamo
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Distributed learning
extremely randomized trees
privacy-preserving machine learning
structured health data
federated machine learning
Online Access:https://ieeexplore.ieee.org/document/9676691/

Internet

https://ieeexplore.ieee.org/document/9676691/

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