# The Holistic Perspective of the INCISIVE Project--Artificial Intelligence in Screening Mammography
## 2 Relevance and Challenges
### Legal Challenges
The project's ambition is to develop a legal framework, which enables data providers to share data with other researchers, using federated and hybrid infrastructure. This INCISIVE approach will allow data providers to retain control over their shared data, hosted in their own secure computing environment. The data provider may also use a dedicated central environment for storing their data (hybrid approach). However, adapting the federated approach to the full extent has some trade-offs [20], which need to be considered both from a practical and legal perspective. This will be addressed in the data-sharing legal framework, which will be one of the results of the project. The goal of the INCISIVE repository is to enable the secure sharing of data in compliance with ethical, legal, and privacy demands, consequently increasing accessibility to datasets for various stakeholders and enabling the experimentation of AI-based solutions. Currently, efforts focus on aligning the requirements of AI researchers, FAIR (findable, available, interoperable, and reusable) principles [21], as well as transparent data sharing and privacy considerations, which are all focal points for the design of the environment. The study takes also into account the alignment of the structure of data sharing with the existing and planned legal acts, including, but not limited to, GDPR [15], the Data Governance Act [22], the Digital Markets Act [23], proposals for the AI Act [24], and European Health Data Space regulations [25]. Those provisions are considered in relation to possible data governance structures, requirements, and processes for platform registration, as well as the use and terms of data sharing. In the process of development and evaluation of the INCISIVE AI-based toolbox, three distinct Study Protocols were needed:  
1. A retrospective study--the model training/development of the INCISIVE AI toolbox. 2. A prospective observational study--the validation of the INCISIVE AI toolbox. 3. A prospective feasibility study--the evaluation of the INCISIVE AI toolbox. Through a rigorous collaborative approach, all aspects of each of the study protocols, including the ethical considerations, have been discussed and agreed upon collaboratively between the relevant consortium partners and, where necessary, the whole consortium. The challenge in relation to the ethical considerations of the three studies stemmed primarily from the diverse processes in place for seeking ethical approval in the five countries where the studies would be deployed. Because of this diversity, it was decided that general ethical template resources would be provided to the stakeholders which can be later modified and adjusted to the specific local requirements and processes in place. Another challenge, in this context, was the diverse group of the target populations. As these include patients, clinicians, and technical personnel, all the appropriate ethical documentation should accommodate the different ethical considerations and hence correspond to their diverse status. The international good practices for the evaluation of technological solutions have informed the decision-making process [16]. The first stage of the development phase included internal meetings to decide on the most appropriate methodology for the study protocols and explore what ethical implications need to be taken into consideration. Things that were taken into consideration in this process included the aim of the study, the type of the intervention to be applied in the clinical setting (e.g., whether the INCISIVE generates ethical concerns in relation to data management), modalities to be assessed, tools to collect the required data (e.g., GDPR principles), ethical issues (e.g., consent forms, withdrawal forms) the type of users, and the variations of the recruitment sites (e.g., recruitment strategy) where the INCISIVE system would be deployed.