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CORDIS - Forschungsergebnisse der EU
CORDIS

Synthetic and scalable data platform for medical empowered AI

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Dissemination and Communication Plan – Version 1.0 (öffnet in neuem Fenster)

Core document outlining the impact-enabling approach, activities, channels (website and social media profiles), tools and timing at the basis of the project’s D&C outreaching strategy, the internal communication processes, templates, responsibilities, KPIs and operative plan for action.

Project website (öffnet in neuem Fenster)

Project public website for dissemination of project news events and results and connection with project and partners social medias

Piloting planning and monitoring approach (öffnet in neuem Fenster)

Document gathering all the requirements needed to guarantee appropriate implementation of the use cases and management of users’ data. This document will include the definition of the legally and ethically compliant engagement process for each end-user, modules/ formats/ checklist/ guidelines for the correct deployment and usage of the developed modules in the platform experimentation. In addition, specific objectives and KPIs for each testing iteration will be defined, as well as the specific timing, minimal configurations (e.g., technical configuration, number, approach for feedback collections, etc.) and tools (e.g. questionnaires, comparison approaches) for KPIs measurement.

State of the Art Report (Suntheti data generation) (öffnet in neuem Fenster)

Report comprising an in-depth survey of the SOA approaches that have been developed for synthetic data generation, providing a strong basis that will guide the research conducted during the project.

State of the art report (Data model auditing) (öffnet in neuem Fenster)

Analysis of the state of the art for data model auditing, including complete literature review, scouting of relevant R&I projects’ results as well as market solution, and selection of most relevant contributions to be used for AISym4Med (e.g. model/algorithm and how to be applied within the platform)

Legal and ethical requirements report and updates (öffnet in neuem Fenster)

Analysis of legal references relevant for the platform ethical assessment and list of mandatory requirements and corresponding strategies to implement them including in annex any templateformat needed eg informed consent model and matchmaking of these requirements with the corresponding SW components

Veröffentlichungen

synple: A Platform for Privacy Preserving Synthetic Patient Data Generation (öffnet in neuem Fenster)

Autoren: Silveira, I., Silva. L., Veladas. F, Braga, R. & Gamboa, H.
Veröffentlicht in: 2024, ISBN 978-3-031-63851-0
Herausgeber: Cham: Springer Nature Switzerland
DOI: 10.1007/978-3-031-63851-0_9

Systematic analysis of the impact of label noise correction on ML Fairness (öffnet in neuem Fenster)

Autoren: Silva, I. Oliveira e; Soares, C.; Sousa, I.; Ghani, R.
Veröffentlicht in: 2023, ISBN 978-981-99-8391-9
Herausgeber: Springer, Singapore
DOI: 10.48550/arxiv.2306.15994

Adapting Stable Diffusion Models for Domain-Specific Medical Imaging: A Case Study in Synthetic Retinal Fundus Image Generation (öffnet in neuem Fenster)

Autoren: Façoco, Ivo; Mesquita, Gonçalo; Lúcio, Francisca; Rosado, Luís
Veröffentlicht in: Proceedings of the ECML-PKDD workshop SynDAiTE: Synthetic Data for AI Trustworthiness and Evolution, 2025
Herausgeber: Springer
DOI: 10.5281/ZENODO.17207258

GASTeN: Generative Adversarial Stress Test Networks (öffnet in neuem Fenster)

Autoren: Cunha, L., Soares, C., Restivo, A., Teixeira, L.F.
Veröffentlicht in: 2023, ISBN 978-3-031-30047-9
Herausgeber: Cham: Springer Nature Switzerland
DOI: 10.1007/978-3-031-30047-9_8

Kernel Corrector LSTM (öffnet in neuem Fenster)

Autoren: Tuna, R., Baghoussi, Y., Soares, C., Mendes-Moreira, J.
Veröffentlicht in: 2024
Herausgeber: Cham: Springer Nature Switzerland.
DOI: 10.1007/978-3-031-58553-1_1

Designing for Qualitative Evaluation of Synthetic Medical Data (öffnet in neuem Fenster)

Autoren: Isabella Barbosa Silva; Elsa Oliveira; Ricardo Melo; Luís Rosado; César Gálvez-Barrón; Irene Bernadet Heijink; Sem Hoogteijling; Iñigo Gabilondo
Veröffentlicht in: CHI EA '25: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2025
Herausgeber: ACM
DOI: 10.1145/3706599.3720274

Benchmarking deep neural representations for synthetic data evaluation (öffnet in neuem Fenster)

Autoren: Nuno, Bento; Joana, Rebelo; Marilia, Barandas
Veröffentlicht in: Intelligent Systems with Applications, 2025, ISSN 2667-3053
Herausgeber: ScienceDirect
DOI: 10.1016/J.ISWA.2025.200580

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