The article explores how integrating AI with healthcare data standards like HL7 and FHIR can transform medical data analysis and diagnoses. It proposes a robust, eight-layer architecture that addresses privacy concerns through various components: data storage, secure computation, AI modeling, and governance. Key features include the AI modeling layer that employs differential privacy to safeguard patient information and ensure explainable diagnoses. Furthermore, the architecture integrates continuous monitoring to detect privacy breaches and maintain compliance with regulations, ensuring patient data is used ethically.
Integrating AI with healthcare data standards like HL7 and FHIR can revolutionize medical data analysis and diagnosis while ensuring patient privacy is preserved.
The proposed architecture consists of eight interconnected layers focused on privacy, including components for data storage, secure computation, AI modeling, and governance.
The governance and compliance layer automates access controls and consent verification, enforcing legal adherence to regulations such as HIPAA and GDPR.
Continuous monitoring and auditing ensure the system's integrity, maintaining audit logs and detecting privacy risks in real-time for medical AI applications.
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