On the public citation graph
Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review
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labelled with the one it came from. Neither is a complete citation index — absence here is not
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1 of the 119 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1007/s00500-023-08330-6 (notice 2024-08-21).
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Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0);
dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1021/acs.jcim.3c00799openalex-snapshotMELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information
inferredcites →https://doi.org/10.1049/cit2.12287openalex-snapshotData privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things
inferredcites →https://doi.org/10.1109/sp.2019.00065openalex-snapshotComprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
inferredcites →https://doi.org/10.3390/math11143093openalex-snapshotTowards Efficient and Trustworthy Pandemic Diagnosis in Smart Cities: A Blockchain-Based Federated Learning Approach
inferredcites →https://doi.org/10.3390/s23177476openalex-snapshotEmpowering Precision Medicine: Unlocking Revolutionary Insights through Blockchain-Enabled Federated Learning and Electronic Medical Records
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/ail2.70044openalex-snapshotAI ‐Powered Personalization Across Digital Ecosystems: A Trust‐Centric Perspective on Intelligent, Ethical, and Adaptive User‐Centric Systems
inferred← citeshttps://doi.org/10.1109/access.2026.3734094openalex-snapshotBeDaSH+: A Comprehensive Framework for Blockchain-Enabled Data-Driven Telehealth Security With Federated Learning, TinyML, and GDPR Compliance
inferred← citeshttps://doi.org/10.2196/95788openalex-snapshotCorrection: Securing Federated Learning With Blockchain in the Medical Field: Systematic Literature Review
inferred← citeshttps://doi.org/10.3390/diagnostics16193171openalex-snapshotArtificial Intelligence-Enabled Medical Diagnosis in the Internet of Medical Things: An End-to-End Survey of Connected Sensing, Distributed Intelligence, Clinical Applications, and Validation
inferred← citeshttps://doi.org/10.47670/wuwijar20262vnrkamkopenalex-snapshotMultimodal and Explainable Artificial Intelligence for Precision Healthcare: Integrating Federated Learning, Governance, and Affective Computing
inferred← citeshttps://doi.org/10.62411/faith.3048-3719-447openalex-snapshotBlockchain-Enabled Federated Learning for Healthcare: An Empirical Evaluation of the Integrity Boundary, Byzantine Robustness, and Ledger Overhead
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