A reliable and privacy-preserved federated learning framework for real-time smoking prediction in healthcare

A reliable and privacy-preserved federated learning framework for real-time smoking prediction in healthcare

The ever-evolving domain of machine learning has witnessed significant advancements with the advent of federated learning, a paradigm revered for its capacity to facilitate model training on decentralized data sources while upholding data confidentiality. This research introduces a federated learnin...

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Bibliographic Details
Main Authors: Siddhesh Fuladi, D. Ruby, N. Manikandan, Animesh Verma, M. K. Nallakaruppan, Shitharth Selvarajan, Preeti Meena, V. P. Meena, Ibrahim A. Hameed
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Computer Science
Subjects:
federated learning
machine learning
privacy preservation
decentralized data
enhanced data security
data preprocessing
Online Access:https://www.frontiersin.org/articles/10.3389/fcomp.2024.1494174/full
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