Cover Image
QR Code

Describing Data Processing in FHIR: AI-Assisted Interoperability for Cancer Stage Extraction...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.

Introduction: Creating interoperable clinical data models in FHIR is essential but often labor-intensive. This study explores the use of Generative AI to assist in documenting and structuring FHIR-based data transformation workflows, focusing on TNM cancer staging extraction. Methods: Using FHIR Rel...

Full description

Published in:Studies in Health Technology & Informatics Vol. 336; pp. 884 - 889
Main Authors: OUAGNE, David, ZOSSOU, Vincent, RANCE, Bastien
Format: proceedings research tables/charts Journal Article
Published: Sage Publications Inc. 2026
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194018943&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 194018943
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        09269630
        U1V
      jtl: Studies in Health Technology & Informatics
      issn: 09269630
      maglogo: N
    pubinfo:
      dt: 2026
      vid: 336
      pid: 344
      pub: Sage Publications Inc.
      place: Thousand Oaks, California
    artinfo:
      ui:
        194018943
        194018943
        194018943
        10.3233/SHTI260306
        194018943
      ppf: 884
      ppct: 5
      formats:
      tig:
        atl: Describing Data Processing in FHIR: AI-Assisted Interoperability for Cancer Stage Extraction...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.
      aug:
        au:
          OUAGNE, David
          ZOSSOU, Vincent
          RANCE, Bastien
        affil: AP-HP, Paris, France.
      sug:
        subj:
          Neoplasm Staging
          Electronic Data Interchange
          Artificial Intelligence, Generative
          Neoplasms Classification
          Health Information Management
          Human
          Congresses and Conferences Italy
          Italy
          Information Storage
          Information Retrieval
          Decision Support Systems, Clinical
          Health Informatics
      ab: Introduction: Creating interoperable clinical data models in FHIR is essential but often labor-intensive. This study explores the use of Generative AI to assist in documenting and structuring FHIR-based data transformation workflows, focusing on TNM cancer staging extraction. Methods: Using FHIR Release 4 and the Plan Definition resource, we modeled transformation processes defined through Business Process Model and Notation (BPMN). The large language model Claude Code (Sonnet 4.5) generated FHIR artifacts from BPMN inputs, which were validated through syntax checks, Implementation Guide compilation, and expert review. Results: AI-assisted generation produced a validated Plan Definition with seven structured activities, accurately representing the TNM extraction workflow. Artifacts were interoperable and passed all FHIR conformance tests after minor revisions. Conclusion / Discussion: Generative AI can effectively support FHIR workflow modeling, reducing complexity and development time. However, expert validation remains essential to ensure semantic accuracy and reproducibility.
      pubtype: Academic Journal
      doctype:
        proceedings
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N