A review of privacy enhancement methods for federated learning in healthcare systems
Federated learning (FL) provides a distributed machine learning system that enables
participants to train using local data to create a shared model by eliminating the requirement …
participants to train using local data to create a shared model by eliminating the requirement …
Privacy-preserving federated recurrent neural networks
We present RHODE, a novel system that enables privacy-preserving training of and
prediction on Recurrent Neural Networks (RNNs) in a cross-silo federated learning setting …
prediction on Recurrent Neural Networks (RNNs) in a cross-silo federated learning setting …
[HTML][HTML] FLCMC: Federated Learning Approach for Chinese Medicinal Text Classification
G Hu, X Fang - Entropy, 2024 - pmc.ncbi.nlm.nih.gov
Addressing the privacy protection and data sharing issues in Chinese medical texts, this
paper introduces a federated learning approach named FLCMC for Chinese medical text …
paper introduces a federated learning approach named FLCMC for Chinese medical text …
Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem
Ł Erimus, A Borowska, A Jaromin… - … on Human System …, 2024 - ieeexplore.ieee.org
We are increasingly striving to introduce modern artificial intelligence techniques in
medicine and elevate medical care, catering to both patients and specialists. An essential …
medicine and elevate medical care, catering to both patients and specialists. An essential …
Investigating privacy-preserving machine learning for healthcare data sharing through federated learning
SK Ahamed, N Nishant, A Selvaraj… - The Scientific …, 2023 - scientifictemper.com
Abstract Privacy-Preserving Machine Learning (PPML) is a pivotal paradigm in healthcare
research, offering innovative solutions to the challenges of data sharing and privacy …
research, offering innovative solutions to the challenges of data sharing and privacy …
Privacy-Preserving Machine Learning for E-Health Applications: A Survey
J Romeo, M Abbass, A Sherif… - 2024 IEEE 3rd …, 2024 - ieeexplore.ieee.org
As more information about people's health is gath-ered and analyzed, privacy concerns
have become increasingly essential. This paper summarizes how machine learning (ML) …
have become increasingly essential. This paper summarizes how machine learning (ML) …
Privacy-preserving federated neural network training and inference
S Sav - 2023 - infoscience.epfl.ch
Training accurate and robust machine learning models requires a large amount of data that
is usually scattered across data silos. Sharing, transferring, and centralizing the data from …
is usually scattered across data silos. Sharing, transferring, and centralizing the data from …