Mamba-fusion for privacy-preserving disease prediction

Mamba-fusion for privacy-preserving disease prediction

Abstract Accurate disease prediction is essential for improving patient outcomes. Privacy regulations like GDPR and HIPAA limit data sharing, hindering the development of robust predictive models across institutions. FL and multi-modal fusion frameworks counter these problems but are restricted in s...

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Bibliographic Details
Main Authors: Muhammad Kashif Jabbar, Huang Jianjun, Ayesha Jabbar, Anas Bilal
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Privacy-preserving federated learning
Multi-modal data fusion
Hierarchical aggregation mechanism
Chronic disease prediction
Differential privacy in healthcare
Scalable healthcare analytics
Online Access:https://doi.org/10.1038/s41598-025-06306-0
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https://doi.org/10.1038/s41598-025-06306-0

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