Advancing Healthcare 5.0 through Federated Learning: Opportunity for Security Enforcement using Blockchain

As Healthcare 5.0 becomes more widely accepted, the healthcare industry in general is changing, leading to better patient care and more system efficiency. The degree of digital automation that introduced cutting-edge technology applications to the health sector is seriously challenged by this shift. Concerns over patient’s privacy and security are heightened by the rising digitization of healthcare institutions, which makes it harder to collaborate and share data seamlessly. The exponential growth of healthcare data necessitates effective processing and analysis in order to maximize patient outcomes and healthcare delivery. To fully realize the potential of Healthcare 5.0, healthcare practitioners, information technology specialists, data scientists, and researchers must address these complex security difficulties. Healthcare 5.0 provides a comprehensive solution to the pressing issues facing the digitalized healthcare industry by thoroughly examining its foundational principles and exploring its practical implementation through cloud computing, data analytics, and federated learning. Through healthcare federated learning, the national electronic health (e-health) policy and strategy will be legitimized. In this paper, the authors categorized and combined healthcare technology with federated learning artificial intelligence (AI) at various automation stages. The paper discussed the issues that are now facing the healthcare industry, such as security, privacy and dependability. The paper provided readers with guidance on how to use AI and federated learning to solve healthcare information system synchronization. In conclusion, the authors discussed broad security topics and future research in the healthcare management system utilizing federated learning and blockchain approach.

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Publication Details

Published
2024-09-26
DOI
https://doi.org/10.23919/softcom62040.2024.10722012
Citations
9
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
7.01
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article

Advancing Healthcare 5.0 through Federated Learning: Opportunity for Security Enforcement using Blockchain

Muhammad Shoaib Ayub, Pablo Adasme, Demóstenes Zegarra Rodríguez, Renata Lopes Rosa et al.
9 citations
Blockchain Technology Applications and Security
7.01
article

Advancing Healthcare 5.0 through Federated Learning: Opportunity for Security Enforcement using Blockchain

Muhammad Shoaib Ayub, Pablo Adasme, Demóstenes Zegarra Rodríguez, Renata Lopes Rosa, Ugochukwu O. Mathew
article en
9 citations

Abstract

As Healthcare 5.0 becomes more widely accepted, the healthcare industry in general is changing, leading to better patient care and more system efficiency. The degree of digital automation that introduced cutting-edge technology applications to the health sector is seriously challenged by this shift. Concerns over patient’s privacy and security are heightened by the rising digitization of healthcare institutions, which makes it harder to collaborate and share data seamlessly. The exponential growth of healthcare data necessitates effective processing and analysis in order to maximize patient outcomes and healthcare delivery. To fully realize the potential of Healthcare 5.0, healthcare practitioners, information technology specialists, data scientists, and researchers must address these complex security difficulties. Healthcare 5.0 provides a comprehensive solution to the pressing issues facing the digitalized healthcare industry by thoroughly examining its foundational principles and exploring its practical implementation through cloud computing, data analytics, and federated learning. Through healthcare federated learning, the national electronic health (e-health) policy and strategy will be legitimized. In this paper, the authors categorized and combined healthcare technology with federated learning artificial intelligence (AI) at various automation stages. The paper discussed the issues that are now facing the healthcare industry, such as security, privacy and dependability. The paper provided readers with guidance on how to use AI and federated learning to solve healthcare information system synchronization. In conclusion, the authors discussed broad security topics and future research in the healthcare management system utilizing federated learning and blockchain approach.

Universidad de Santiago de Chile (CL), Universidade Federal de Lavras (BR)
Reduced inequalities
Openalex Percentile: Top 3%
Blockchain Technology Applications and Security
7.01
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