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

Información del proyecto

INSAFEDARE

Identificador del acuerdo de subvención: 101095661

DOI

10.3030/101095661

Fecha de la firma de la CE 8 Noviembre 2023

Fecha de inicio 1 Noviembre 2023

Fecha de finalización 31 Octubre 2026

Financiado con arreglo a

• Health

Coste total

€ 2 855 645,00

Aportación de la UE

€ 2 855 645,00

Coordinado por

COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
France

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

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.

Publicaciones

Conference proceedings (5)

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

Autores: 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
Publicado en: Studies in Health Technology and Informatics, Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024
Editor: IOS Press
DOI: 10.3233/SHTI240624

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

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

Preliminary Results on Improved Synthetic Image Generation for Melanoma Skin Cancer

Autores: Saadullah Farooq Abbasi, Muhammad Bilal, Teesta Mukherjee, Saif ul Islam, Omid Pournik, Theodoros N. Arvanitis
Publicado en: Studies in Health Technology and Informatics, Envisioning the Future of Health Informatics and Digital Health, 2025
Editor: 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

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

Deep Learning-Based Synthetic Skin Lesion Image Classification

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

Peer reviewed articles (1)

Fidelity-agnostic synthetic data generation improves utility while retaining privacy

Autores: Jim Achterberg, Marcel Haas, Bram van Dijk, Marco Spruit
Publicado en: Patterns, 2025, ISSN 2666-3899
Editor: Elsevier BV
DOI: 10.1016/J.PATTER.2025.101287