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Analysis of AI challenges related to cancer imaging while striving to achieve a highly acceptable solution

INCISIVE will focus on the different target users (healthcare providers (e.g. radiologists, oncologists etc) by thoroughly analyzing all parameters, gaps and challenges related with the use of imaging in cancer diagnosis, prediction and follow-up. INCISIVE will follow the entire journey of how data is being utilized to support treatment strategies and will identify key pain points of the various stakeholders that will be addressed. The analysis will take into account the user needs and experiences, the currently established pathways, the procedures followed, legal implications related to privacy, security and data sharing, and finally the availability of data. The target result is an effective and scalable design of the INCISIVE AI-driven tools, imaging repository and solution-as-a-whole. This pillar consists of the following objectives:


Objective 1.1
To thoroughly analyze the challenges related to the wide adoption of AI solutions for medical imaging: including how these can applied in current medical practice for cancer diagnosis, prediction and follow-up, taking into account in a structured way the views and experiences of INCISIVE stakeholders and publicly available data.
Objective 1.2
To assess currently existing care pathways and scanning solutions: This will be based on interactive sessions and focus groups with INCISIVE primary users (healthcare professionals) towards identifying gaps and needs, as well as a thorough market and healthcare systems scanning. The heterogeneity in the healthcare service provision among different countries will be taken into account.
Objective 1.3
To define INCISIVE scenarios of use: illustrating the end-to-end INCISIVE functionalities from the user perspective in order to cover the defined user requirements/need.
Objective 1.4
To design in detail INCISIVE system and components architecture: based on established standards, following well-known design practices, incorporating security-by-design and ensuring scalability and good performance of the foreseen functionalities, reinforcing the acceptability of the solution

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