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Effect of incorporating metadata to the generation of synthetic time series in a healthcare context.

, , , , , , , and . CBMS, page 910-916. IEEE, (2023)

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Standardized and extensible reference data model for clinical research in Living Labs., , , , , , , and . EUSPN/ICTH, volume 210 of Procedia Computer Science, page 165-172. Elsevier, (2022)Comparative Evaluation of Oversampling Techniques for Balancing Metabolic Profiles., , , , , , and . ICBRA, page 41-47. ACM, (2022)Effect of incorporating metadata to the generation of synthetic time series in a healthcare context., , , , , , , and . CBMS, page 910-916. IEEE, (2023)Comparative assessment of synthetic time series generation approaches in healthcare: leveraging patient metadata for accurate data synthesis., , , , , , , , and . BMC Medical Informatics Decis. Mak., 24 (1): 27 (December 2024)Synthetic data generation for tabular health records: A systematic review., , , , and . Neurocomputing, (2022)Privacy Mechanisms and Evaluation Metrics for Synthetic Data Generation: A Systematic Review., , , , , and . IEEE Access, (2024)A Secure Data Publishing and Access Service for Sensitive Data from Living Labs: Enabling Collaboration with External Researchers via Shareable Data., , , , , , , , , and 1 other author(s). Big Data Cogn. Comput., 8 (6): 55 (2024)Differentially Private Non Parametric Copulas: Generating synthetic data with non parametric copulas under privacy guarantees., , , , and . CoRR, (2024)