Health Information Technology Commons^™

Architectural Design Of A Blockchain-Enabled, Federated Learning Platform For Algorithmic Fairness In Predictive Health Care: Design Science Study, Xueping Liang, Juan Zhao, Yan Chen, Eranga Bandara, Sachin Shetty

VMASC Publications

Background: Developing effective and generalizable predictive models is critical for disease prediction and clinical decision-making, often requiring diverse samples to mitigate population bias and address algorithmic fairness. However, a major challenge is to retrieve learning models across multiple institutions without bringing in local biases and inequity, while preserving individual patients' privacy at each site.

Objective: This study aims to understand the issues of bias and fairness in the machine learning process used in the predictive health care domain. We proposed a software architecture that integrates federated learning and blockchain to improve fairness, while maintaining acceptable prediction accuracy and minimizing overhead …

Healthcare 5.0 Security Framework: Applications, Issues And Future Research Directions, Mohammad Wazid, Ashok Kumar Das, Noor Mohd, Youngho Park

VMASC Publications

Healthcare 5.0 is a system that can be deployed to provide various healthcare services. It does these services by utilising a new generation of information technologies, such as Internet of Things (IoT), Artificial Intelligence (AI), Big data analytics, blockchain and cloud computing. Due to the introduction of healthcare 5.0, the paradigm has been now changed. It is disease-centered to patient-centered care where it provides healthcare services and supports to the people. However, there are several security issues and challenges in healthcare 5.0 which may cause the leakage or alteration of sensitive healthcare data. This demands that we need a robust …