Abstract:
The paper delves into the synergy between blockchain technology and Artificial intelligence and machine learning (AIML)
tools in healthcare information exchange, with a focus on privacy-preserving data visualization. Acknowledging patients’ ownership of
healthcare data and the imperative to maintain confidentiality, the study addresses challenges in data analysis for governmental bodies.
To overcome this, the paper proposes integrating AIML tools with blockchain networks, leveraging blockchain’s decentralized nature
and AIML’s analytical capabilities. Patients retain control over their data, ensuring confidentiality and access control. The paper outlines
the implementation process, highlighting challenges and mitigation strategies. It discusses limitations, including technical complexities
and regulatory constraints, and presents results demonstrating the framework’s efficacy in preserving privacy while enabling data
visualization. Future research directions include scalability improvements and regulatory frameworks. Ultimately, the paper emphasizes
the transformative potential of blockchain-AIML collaboration in fostering a transparent, patient-centric healthcare ecosystem, aligning
cutting-edge technology with privacy and security imperatives. Additionally, the study explores various use cases and real-world
applications of the proposed framework, showcasing how it can be adapted to different healthcare scenarios. By integrating blockchain
and AIML, the paper underscores the importance of interdisciplinary approaches in addressing contemporary healthcare challenges. The
collaborative efforts of stakeholders, including technologists, healthcare professionals, and policymakers, are crucial for the successful
adoption and implementation of this innovative framework.