Dicing with data: the risks, benefits, tensions and tech of health data in the iToBoS project

Partners in the iToBoS consortium recently had their work published in a peer reviewed scientific journal, entitled Frontiers in Digital Health.

Reflections about data sharing in the healthcare sector

Actors from different sectors, backgrounds and involvement with the acquisition, access and management of health data met in Berlin in the context of the MPNE 2024 Consensus in the framework of the iToBoS project.

Perspectives for Generative AI at MPNE Consensus on Data Workshop

Berlin, 1/02/2024.

Presentation of the perspectives of generative Artificial Intelligence in melanoma at the MPNEconsensus 2024 by the iToBoS partner Leibniz University Hannover.

Transformers in Dermoscopic Image Classification

Dermoscopy is a powerful method used in dermatology to analyze the features of skin lesions.

Semi-Supervised Learning

Semi-supervised learning is a type of machine learning paradigm that falls between supervised and unsupervised learning.

Assessing and Implementing Trustworthy AI Across Multiple Dimensions

Artificial intelligence (AI) systems have become more and more prevalent in everyday life and especially in enterprise settings.

Melanoma Education with Generative AI in Dermatology

As artificial intelligence (AI) rapidly advances, its integration into dermatology, particularly through Generative Adversarial Networks (GANs), is opening new horizons in patient education and skin cancer diagnosis.

European Commission and WHO/Europe form partnership agreement for Data Sharing and Governance

The iToBoS project has previously written on the emergence of policy initiatives, regulatory frameworks and legislative proposals concerning a European Health Data Space [1].


Multimodal learning is the challenging task of using data from various modalities to improve the capacity of one model.