INNOVATIVE APPLICATIONS OF ASSESSMENT AND ASSURANCE OF DATA AND SYNTHETIC DATA FOR REGULATORY DECISION SUPPORT

Informations projet

INSAFEDARE

N° de convention de subvention: 101095661

DOI

10.3030/101095661

Date de signature de la CE 8 Novembre 2023

Date de début 1 Novembre 2023

Date de fin 31 Octobre 2026

Financé au titre de

• Health

Coût total

€ 2 855 645,00

Contribution de l’UE

€ 2 855 645,00

Coordonné par

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
France

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Websites, patent fillings, videos etc. (1)

Project website

Project website.

Other (1)

Data Integration Pipeline Tools

Data Integration Pipeline Tools.

Documents, reports (1)

Literature review and classification of digital health applications

Literature review and classification of digital health applications.

Publications

Conference proceedings (6)

INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support

Auteurs: Parisis Gallos, Nicholas Matragkas, Saif ul Islam, Gregory Epiphaniou, Scott Hansen, Stuart Harrison, Bram van Dijk, Marcel Haas, Giorgos Pappous, Simon Brouwer, Francesco Torlontano, Saadullah Farooq Abbasi, Omid Pournik, James Churm, John Mantas, Carlos Luis Parra-Calderón, Dimitrios Petkousis, Patrick Weber, Benjamin Dzingina, Chokri Mraidha, Carsten Maple, Jim Achterberg, Marco Spruit, Evi Saratsioti, Younes Moustaghfir, Theodoros N. Arvanitis
Publié dans: Studies in Health Technology and Informatics, Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024
Éditeur: IOS Press
DOI: 10.3233/SHTI240624

A Novel Taxonomy for Navigating and Classifying Synthetic Data in Healthcare Applications

Auteurs: Bram van Dijk; Saif ul Islam; Jim Achterberg; Hafiz Muhammad Waseem; Parisis Gallos; Gregory Epiphaniou; Carsten Maple; Marcel Haas; Marco Spruit
Publié dans: Studies in Health Technology and Informatics ISBN: 9781643685540, 2024
Éditeur: IOS Press
DOI: 10.48550/ARXIV.2409.00701

Preliminary Results on Improved Synthetic Image Generation for Melanoma Skin Cancer

Auteurs: Saadullah Farooq Abbasi, Muhammad Bilal, Teesta Mukherjee, Saif ul Islam, Omid Pournik, Theodoros N. Arvanitis
Publié dans: Studies in Health Technology and Informatics, Envisioning the Future of Health Informatics and Digital Health, 2025
Éditeur: IOS Press
DOI: 10.3233/SHTI250081

Characterizing a Framework for Assessment of the Use of FAIR Principles for Health Data in Digital Health Devices Regulation

Auteurs: Carlos Luis Parra-Calderón, Giulia Finocchiaro, Saif ul Islam, Stuart Harrison, Gregory Epiphaniou, Carsten Maple, Parisis Gallos
Publié dans: Studies in Health Technology and Informatics, Envisioning the Future of Health Informatics and Digital Health, 2025
Éditeur: IOS Press
DOI: 10.3233/SHTI250093

The Data Sharing Paradox of Synthetic Data in Healthcare

Auteurs: Jim Achterberg, Bram van Dijk, Saif ul Islam, Hafiz Muhammad Waseem, Parisis Gallos, Gregory Epiphaniou, Carsten Maple, Marcel Haas, Marco Spruit
Publié dans: Studies in Health Technology and Informatics
Éditeur: IOS Press
DOI: 10.48550/ARXIV.2503.20847

Deep Learning-Based Synthetic Skin Lesion Image Classification

Auteurs: Saadullah Farooq Abbasi, Muhammad Bilal, Teesta Mukherjee, James Churm, Omid Pournik, Gregory Epiphaniou, Theodoros N. Arvanitis
Publié dans: Studies in Health Technology and Informatics, Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024
Éditeur: IOS Press
DOI: 10.3233/SHTI240612

Peer reviewed articles (1)

Fidelity-agnostic synthetic data generation improves utility while retaining privacy

Auteurs: Jim Achterberg, Marcel Haas, Bram van Dijk, Marco Spruit
Publié dans: Patterns, 2025, ISSN 2666-3899
Éditeur: Elsevier BV
DOI: 10.1016/J.PATTER.2025.101287