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Architectural Design of a Blockchain-Enabled, Federated Learning Platform for Algorithmic Fairness in Predictive Health Care: Design Science Study

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/jama.290.18.2487-bopenalex-snapshot
Health Care Disparities
inferredcites →https://doi.org/10.1001/jamanetworkopen.2021.3909openalex-snapshot
Comparison of Methods to Reduce Bias From Clinical Prediction Models of Postpartum Depression
inferredcites →https://doi.org/10.1002/9780471462422.eoct478openalex-snapshot
National Institutes of Health ( NIH )
inferredcites →https://doi.org/10.1007/978-981-15-2777-7_35openalex-snapshot
Aplos: Smart Contracts Made Smart
inferredcites →https://doi.org/10.1007/978-981-19-2976-2openalex-snapshot
Blockchain in Life Sciences
inferredcites →https://doi.org/10.1007/978-981-19-2976-2_6openalex-snapshot
A Blockchain-Empowered Federated Learning System and the Promising Use in Drug Discovery
inferredcites →https://doi.org/10.1016/j.cie.2020.106854openalex-snapshot
A review of applications in federated learning
inferredcites →https://doi.org/10.1016/j.dss.2012.08.007openalex-snapshot
Design and evaluation of Ubiquitous Information Systems and use in healthcare
inferredcites →https://doi.org/10.1016/j.dss.2012.10.003openalex-snapshot
Health information technology and its impact on the quality and cost of healthcare delivery
inferredcites →https://doi.org/10.1016/j.dss.2013.03.002openalex-snapshot
Analyzing the enabling factors for the organizational decision to adopt healthcare information systems
inferredcites →https://doi.org/10.1016/j.dss.2017.05.011openalex-snapshot
Designing utilization-based spatial healthcare accessibility decision support systems: A case of a regional health plan
inferredcites →https://doi.org/10.1016/j.dss.2018.02.007openalex-snapshot
Cyber-analytics: Modeling factors associated with healthcare data breaches
inferredcites →https://doi.org/10.1016/j.eswa.2020.113406openalex-snapshot
A comparative evaluation of aggregation methods for machine learning over vertically partitioned data
inferredcites →https://doi.org/10.1016/j.jbi.2021.103748openalex-snapshot
ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes
inferredcites →https://doi.org/10.1016/j.jbi.2023.104294openalex-snapshot
Evaluating and mitigating bias in machine learning models for cardiovascular disease prediction
inferredcites →https://doi.org/10.1016/j.jisa.2021.102949openalex-snapshot
Privacy preservation in Distributed Deep Learning: A survey on Distributed Deep Learning, privacy preservation techniques used and interesting research directions
inferredcites →https://doi.org/10.1016/j.sysarc.2021.102061openalex-snapshot
Rahasak—Scalable blockchain architecture for enterprise applications
inferredcites →https://doi.org/10.1038/s41586-019-1390-1openalex-snapshot
A clinically applicable approach to continuous prediction of future acute kidney injury
inferredcites →https://doi.org/10.1038/s41586-021-03583-3openalex-snapshot
Swarm Learning for decentralized and confidential clinical machine learning
inferredcites →https://doi.org/10.1038/s41598-018-36745-xopenalex-snapshot
Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction
inferredcites →https://doi.org/10.1038/s41746-020-0304-9openalex-snapshot
Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities
inferredcites →https://doi.org/10.1038/s43856-022-00165-wopenalex-snapshot
Subpopulation-specific machine learning prognosis for underrepresented patients with double prioritized bias correction
inferredcites →https://doi.org/10.1055/s-0039-1677908openalex-snapshot
AI in Health: State of the Art, Challenges, and Future Directions
inferredcites →https://doi.org/10.1056/nejm200309253491321openalex-snapshot
Book Review Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care Edited by Brian D. Smedley, Adrienne Y. Stith, and Alan R. Nelson. 764 pp. Washington, D.C., National Academies Press, 2003. $79.95. 0-309-08532-2
inferredcites →https://doi.org/10.1056/nejmlim035027openalex-snapshot
HIPAA Regulations — A New Era of Medical-Record Privacy?
inferredcites →https://doi.org/10.1093/jamia/ocy017openalex-snapshot
Distributed deep learning networks among institutions for medical imaging
inferredcites →https://doi.org/10.1097/00115514-200905000-00009openalex-snapshot
Strategic, Political, and Cultural Aspects of IT Implementation: Improving the Efficacy of an IT System in a Large Hospital
inferredcites →https://doi.org/10.1108/idd-01-2021-0010openalex-snapshot
A blockchain-based information management system for academic institutions: a case study of international students’ workflow
inferredcites →https://doi.org/10.1109/allerton.2016.7852293openalex-snapshot
Hypothesis testing in the high privacy limit
inferredcites →https://doi.org/10.1109/ccnc49033.2022.9700513openalex-snapshot
Bassa-ML — A Blockchain and Model Card Integrated Federated Learning Provenance Platform
inferredcites →https://doi.org/10.1109/jiot.2019.2923261openalex-snapshot
Secure Data Aggregation of Lightweight E-Healthcare IoT Devices With Fair Incentives
inferredcites →https://doi.org/10.1109/jiot.2022.3144450openalex-snapshot
Toward Trustworthy AI: Blockchain-Based Architecture Design for Accountability and Fairness of Federated Learning Systems
inferredcites →https://doi.org/10.1109/ms.2015.11openalex-snapshot
Microservices
inferredcites →https://doi.org/10.1111/isj.12370openalex-snapshot
A sociotechnical view of algorithmic fairness
inferredcites →https://doi.org/10.1126/science.aax2342openalex-snapshot
Dissecting racial bias in an algorithm used to manage the health of populations
inferredcites →https://doi.org/10.1145/1773912.1773922openalex-snapshot
Cassandra
inferredcites →https://doi.org/10.1145/3287560.3287567openalex-snapshot
Problem Formulation and Fairness
inferredcites →https://doi.org/10.1145/3352020.3352024openalex-snapshot
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark
inferredcites →https://doi.org/10.1145/3376898openalex-snapshot
A snapshot of the frontiers of fairness in machine learning
inferredcites →https://doi.org/10.1145/3457607openalex-snapshot
A Survey on Bias and Fairness in Machine Learning
inferredcites →https://doi.org/10.1145/3519420openalex-snapshot
Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspective
inferredcites →https://doi.org/10.1145/872757.872771openalex-snapshot
Information sharing across private databases
inferredcites →https://doi.org/10.1147/jrd.2019.2942287openalex-snapshot
AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias
inferredcites →https://doi.org/10.1197/jamia.m2475openalex-snapshot
Identifying Organizational Capacities and Incentives for Clinical Data-sharing: The Case of a Regional Perinatal Information System
inferredcites →https://doi.org/10.1201/9781439816158-1openalex-snapshot
Introduction
inferredcites →https://doi.org/10.1287/isre.2020.0990openalex-snapshot
Crowds, Lending, Machine, and Bias
inferredcites →https://doi.org/10.1287/mnsc.2016.2643openalex-snapshot
Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them
inferredcites →https://doi.org/10.1287/mnsc.2021.4065openalex-snapshot
'Un'Fair Machine Learning Algorithms
inferredcites →https://doi.org/10.1371/journal.pgen.1000167openalex-snapshot
Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
inferredcites →https://doi.org/10.2196/13598openalex-snapshot
ACTION-EHR: Patient-Centric Blockchain-Based Electronic Health Record Data Management for Cancer Care
inferredcites →https://doi.org/10.2196/13600openalex-snapshot
Privacy-Preserving Methods for Feature Engineering Using Blockchain: Review, Evaluation, and Proof of Concept
inferredcites →https://doi.org/10.2196/18623openalex-snapshot
Combating Health Care Fraud and Abuse: Conceptualization and Prototyping Study of a Blockchain Antifraud Framework
inferredcites →https://doi.org/10.2196/20891openalex-snapshot
Federated Learning on Clinical Benchmark Data: Performance Assessment
inferredcites →https://doi.org/10.2196/24109openalex-snapshot
The Health Care Sector’s Experience of Blockchain: A Cross-disciplinary Investigation of Its Real Transformative Potential
inferredcites →https://doi.org/10.2196/25946openalex-snapshot
A Traditional Chinese Medicine Traceability System Based on Lightweight Blockchain
inferredcites →https://doi.org/10.2196/28613openalex-snapshot
Applications of Blockchain in the Medical Field: Narrative Review
inferredcites →https://doi.org/10.2196/41588openalex-snapshot
Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review
inferredcites →https://doi.org/10.2196/43006openalex-snapshot
Applications of Federated Learning in Mobile Health: Scoping Review
inferredcites →https://doi.org/10.2307/25148625openalex-snapshot
Design Science in Information Systems Research1
inferredcites →https://doi.org/10.25300/misq/2020/14644openalex-snapshot
Connecting Systems, Data, and People: A Multidisciplinary Research Roadmap for Chronic Disease Management
inferredcites →https://doi.org/10.48550/arxiv.2206.14397openalex-snapshot
Fair Machine Learning in Healthcare: A Review

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-19303-2_22openalex-snapshot
Next-Generation Mental Health Monitoring: AI, Blockchain, and Cyber-Physical Systems in Action
inferred← citeshttps://doi.org/10.1007/978-3-032-19981-2_24openalex-snapshot
Blockchain-Enabled Secure Federated Learning for IoMT
inferred← citeshttps://doi.org/10.1007/s10462-025-11475-5openalex-snapshot
A survey on group fairness in federated learning: challenges, taxonomy of solutions and directions for future research
inferred← citeshttps://doi.org/10.1016/j.array.2026.101002openalex-snapshot
Machine learning-integrated private blockchain framework for bias detection in clinical trials data
inferred← citeshttps://doi.org/10.1016/j.imed.2024.09.002openalex-snapshot
2024 Chinese guideline on the construction and application of medical blockchain
inferred← citeshttps://doi.org/10.1016/j.iot.2026.101890openalex-snapshot
Medvault: Privacy-enhancing medical record retrieval for ioMT-Enabled healthcare with query-pattern protection
inferred← citeshttps://doi.org/10.1016/j.suscom.2026.101489openalex-snapshot
Blockchain-Enabled Differentially Private Federated Learning for Secure and Trustworthy Healthcare Data Management
inferred← citeshttps://doi.org/10.1080/03772063.2025.2590756openalex-snapshot
Blockchain-Enhanced Homomorphic Encryption for Neuro-Signal Driven Collaborative Intelligence in Secure Adaptive Learning Environments
inferred← citeshttps://doi.org/10.1101/2025.09.09.25335385openalex-snapshot
Evaluating algorithm Fairness in Predicting Health Service Use and Unmet Need Across Socioeconomic and Caste Subgroups: Evidence from Longitudinal Ageing Study in India
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825652openalex-snapshot
Federated Objective: Assessing Client Truthfulness in Federated Learning
inferred← citeshttps://doi.org/10.1109/cbms65348.2025.00158openalex-snapshot
FairMed-FL: Federated Learning for Fair and Unbiased Deep Learning in Medical Imaging
inferred← citeshttps://doi.org/10.1109/ceect59667.2023.10420790openalex-snapshot
Design and Implementation of a Portable Digital Energy Measurement Field Diagnosis Instrument Based on DBN
inferred← citeshttps://doi.org/10.1109/icesc65114.2025.11212588openalex-snapshot
AI and Blockchain for Secure and Decentralized Healthcare Systems
inferred← citeshttps://doi.org/10.1109/idciot67589.2026.11455871openalex-snapshot
Blockchain-Enabled Federated Learning Framework for Secure, Scalable, and Privacy-Preserving Healthcare AI
inferred← citeshttps://doi.org/10.1109/tccn.2026.3661499openalex-snapshot
CPFL: A Cluster-Based Parallel Blockchain Scheme for Secure and Efficient Federated Learning in Intelligent Connected Vehicles
inferred← citeshttps://doi.org/10.1140/epjs/s11734-026-02475-9openalex-snapshot
Federated learning in healthcare: a review of the deployment gap between simulated and real-world implementations
inferred← citeshttps://doi.org/10.1145/3632634.3655881openalex-snapshot
Enhancing Data Diversity and Traceability to Mitigate Bias in Healthcare AI: A Blockchain-Driven Approach
inferred← citeshttps://doi.org/10.1177/20552076251334422openalex-snapshot
Five steps for the deployment of artificial intelligence-driven healthcare delivery for remote and indigenous populations in Canada
inferred← citeshttps://doi.org/10.2196/80178openalex-snapshot
Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance
inferred← citeshttps://doi.org/10.3389/fmed.2025.1534117openalex-snapshot
Swarm learning network for privacy-preserving and collaborative deep learning assisted diagnosis of fracture: a multi-center diagnostic study
inferred← citeshttps://doi.org/10.3389/fpsyg.2026.1875355openalex-snapshot
Exploring perceived AI substitution in future accounting frameworks: the role of psychological trust, anxiety, and cognitive adaptability
inferred← citeshttps://doi.org/10.3389/fpubh.2026.1762346openalex-snapshot
A robust and verifiable federated learning framework for preventing data poisonous threats in e-health
inferred← citeshttps://doi.org/10.3390/biomedicines13010167openalex-snapshot
From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care
inferred← citeshttps://doi.org/10.3390/fi17110505openalex-snapshot
Resilient Federated Learning for Vehicular Networks: A Digital Twin and Blockchain-Empowered Approach
inferred← citeshttps://doi.org/10.3390/healthcare13212760openalex-snapshot
Federated Learning in Public Health: A Systematic Review of Decentralized, Equitable, and Secure Disease Prevention Approaches
inferred← citeshttps://doi.org/10.3390/s26010229openalex-snapshot
A Systematic Review of Federated and Cloud Computing Approaches for Predicting Mental Health Risks
inferred← citeshttps://doi.org/10.36227/techrxiv.171340632.25905526/v1openalex-snapshot
Integration of Federated Learning and Blockchain in Healthcare: A Tutorial
inferred← citeshttps://doi.org/10.4018/979-8-3373-9730-6.ch016openalex-snapshot
The Use of Blockchain Technology in the Provision of Public Health Service
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