New implementation of data standards for AI in oncology: Experience from the EuCanImage project

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  • dc.contributor.author García-Lezana, Teresa
  • dc.contributor.author Bobowicz, Maciej
  • dc.contributor.author Frid, Santiago
  • dc.contributor.author Rutherford, Michael
  • dc.contributor.author Recuero, Mikel
  • dc.contributor.author Riklund, Katrine
  • dc.contributor.author Cabrelles, Aldar
  • dc.contributor.author Rygusik, Marlena
  • dc.contributor.author Fromont, Lauren A.
  • dc.contributor.author Francischello, Roberto
  • dc.contributor.author Neri, Emanuele
  • dc.contributor.author Capella Gutiérrez, Salvador Jesús, 1985-
  • dc.contributor.author Navarro i Cuartiellas, Arcadi, 1969-
  • dc.contributor.author Prior, Fred
  • dc.contributor.author Bona, Jonathan
  • dc.contributor.author Nicolas, Pilar
  • dc.contributor.author Starmans, Martijn P. A.
  • dc.contributor.author Lekadir, Karim, 1977-
  • dc.contributor.author Rambla de Argila, Jordi
  • dc.date.accessioned 2025-06-06T07:06:45Z
  • dc.date.available 2025-06-06T07:06:45Z
  • dc.date.issued 2025
  • dc.description.abstract Background: An unprecedented amount of personal health data, with the potential to revolutionize precision medicine, is generated at health care institutions worldwide. The exploitation of such data using artificial intelligence (AI) relies on the ability to combine heterogeneous, multicentric, multimodal, and multiparametric data, as well as thoughtful representation of knowledge and data availability. Despite these possibilities, significant methodological challenges and ethicolegal constraints still impede the real-world implementation of data models. Technical details: The EuCanImage is an international consortium aimed at developing AI algorithms for precision medicine in oncology and enabling secondary use of the data based on necessary ethical approvals. The use of well-defined clinical data standards to allow interoperability was a central element within the initiative. The consortium is focused on 3 different cancer types and addresses 7 unmet clinical needs. We have conceived and implemented an innovative process to capture clinical data from hospitals, transform it into the newly developed EuCanImage data models, and then store the standardized data in permanent repositories. This new workflow combines recognized software (REDCap for data capture), data standards (FHIR for data structuring), and an existing repository (EGA for permanent data storage and sharing), with newly developed custom tools for data transformation and quality control purposes (ETL pipeline, QC scripts) to complement the gaps. Conclusion: This article synthesizes our experience and procedures for health care data interoperability, standardization, and reproducibility.
  • dc.description.sponsorship This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 952103.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation García-Lezana T, Bobowicz M, Frid S, Rutherford M, Recuero M, Riklund K, et al. New implementation of data standards for AI in oncology: Experience from the EuCanImage project. Gigascience. 2025 Jan 6;14:giae101. DOI: 10.1093/gigascience/giae101
  • dc.identifier.doi http://dx.doi.org/10.1093/gigascience/giae101
  • dc.identifier.issn 2047-217X
  • dc.identifier.uri http://hdl.handle.net/10230/70634
  • dc.language.iso eng
  • dc.publisher Oxford University Press
  • dc.relation.ispartof Gigascience. 2025 Jan 6;14:giae101
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/952103
  • dc.rights © The Author(s) 2024. Published by Oxford University Press GigaScience. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword FHIR
  • dc.subject.keyword Artificial intelligence
  • dc.subject.keyword Data model
  • dc.subject.keyword Interoperability
  • dc.title New implementation of data standards for AI in oncology: Experience from the EuCanImage project
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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Articles (Departament de Medicina i Ciències de la Vida)
Articles (Center for Genomic Regulation (CRG))
Documents OpenAIRE (Open Access Infrastructure for Research in Europe)