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. 2022 Oct 12;10(10):e40344. doi: 10.2196/40344

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©Santiago Frid, Maria Angeles Fuentes Expósito, Inmaculada Grau-Corral, Clara Amat-Fernandez, Montserrat Muñoz Mateu, Xavier Pastor Duran, Raimundo Lozano-Rubí. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 12.10.2022.

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 use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.

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Information systems within the ASCAPE project. Patients register side effects in Xemio Research, which also tracks patients’ daily steps. These data are standardized using a conversion module within the HCB environment (see the Methodology section, step 3), and it is both stored in the OntoCR and sent to ASCAPE Local Edge, which generates and updates ASCAPE’s AI predictive models, which are shared and evaluated in its accuracy in the federated node. AI: artificial intelligence; ASCAPE: Artificial intelligence Supporting CAncer Patients across Europe; HCB: Hospital Clínic de Barcelona.