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Updated: Jul 4, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Bridging Fragmented PHR Ecosystems Through a Unified Document Terminology
Eizen Kimura1, Tsubasa Takahashi2, Saori Sawada2
1Department of Medical Informatics, Medical School of Ehime University, Japan.
Abstract:
Japan's PHR landscape is fragmented across private vendors, hindering data portability. In the PHOENICS project, we addressed this by adopting FHIR Storage to exchange health data. We identified 30 document types; half lacked internal metadata for schema and versioning. We set up a FHIR CodeSystem naming method to enable document parsers to programmatically identify document types. Our findings highlight the need for stakeholders to keep a central registry for the metadata uniquely identifiable for automated document routing.
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Key Attributes include the following:
