Author(s): Qi Y; Vianna P; Cadrin-ChĂȘnevert A; Blanchet K; Montagnon E; Belilovsky E; Wolf G; Mullie LA; Cloutier G; ChassĂ© M; Tang A;
We aimed to implement four data partitioning strategies evaluated with four federated learning (FL) algorithms and investigate the impact of data distribution on FL model performance in detecting steatosis using B-mode US images. A private dataset (153 patients; 1530 images) and a public dataset ...
Article GUID: 38858500
Author(s): Rjoub G; Wahab OA; Bentahar J; Cohen R; Bataineh AS;
In the context of distributed machine learning, the concept of federated learning (FL) has emerged as a solution to the privacy concerns that users have about sharing their own data with a third-party server. FL allows a group of users (often referred to as clients) to locally train a single machine learning model on their devices without sharing their ra ...
Article GUID: 35875592
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