Technical Name |
Privacy-Preserving Medical Data Warehouse System Supporting Secure Data Mining |
Project Operator |
National Sun Yat-sen University |
Project Host |
范俊逸 |
Summary |
The Privacy-Preserving Medical Data Warehouse System uses the FHIR standard for international medical information exchange. It employs advanced security technologies to protect medical data stored on the public cloud, ensuring safe data sharingreducing maintenance costs. Additionally, it utilizes federated learning to enable cross-institutionaltransnational medical model training while complying with legal restrictions. |
Scientific Breakthrough |
The core technology of the Privacy-Preserving Medical Data Warehouse System Supporting Secure Data Mining is developing an SABHPRE encryption scheme, which allows the public clouds to manage encrypted medical data without losing security. Moreover, through federal learning, patients’ mobile devices become a part of medical model training, forming an intelligent privacy-preserving medical model to achieve intelligent disease preventionprecision medicine. |
Industrial Applicability |
The Privacy-Preserving Medical Data Warehouse System enables easy integration of encryption techniques into various systems, allowing for quick upgrades. It also allows medical institutions to securely upload their data to the public cloud, reducing costs. Additionally, the system's federal learning scheme can be applied to telehealthdiagnosis, ensuring convenient access to high-quality caremedical resources for elderly individuals in remote areas. |
Keyword |
Privacy-Preserving Healthcare Data Electronic Health Record Fast Healthcare Interoperability Resources Functional Encryption Attribute-Based Encryption Privacy-Preserving Computation Homomorphic Encryption Multi-Party Computation Federated Learning |
Notes |
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