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Imaging the Future - Horizon scanning for emerging technologies and breakthrough innovations in the field of medical imaging and AI

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This report documents the process and findings of a horizon scanning exercise, part of a series under the FUTURINNOV (FUTURe-oriented detection and assessment of emerging technologies and break-through INNOVation) project, a collaboration between the European Innovation Council (EIC) and the Joint Research Centre (JRC), aiming to bolster the EIC's strategic intelligence through foresight and anticipatory methodologies. The workshop, held on 17 September 2024, had as its primary goal the evaluation and prioritisation of trends and signals on emerging technologies and breakthrough innovation, across all technology readiness levels (TRLs), within the EIC's Medical Imaging and AI portfolio. Signals for the workshop were gathered from experts, literature review, and text/data mining of patents, publications, and EU-funded projects. These signals were then scrutinised for their significance to the field's future by a diverse group of sector experts which led to the identification of eight key topics: generative AI for healthcare; digital twins; multimodal data analysis; explainable AI in medical imaging; application of AI to specific diseases/conditions; XR - augmented and virtual realities; tensor-valued diffusion encoding, and AI-generated synthetic data for training AI. Furthermore, the workshop identified additional wild cards with high novelty and disruptive potential such as: blockchain, edge computing and differential privacy for secure, AI-driven medical imaging and collaborative healthcare optimisation and quantum medical imaging. Participants also highlighted various factors that could influence the development, adoption, and pro-motion of these emerging technologies, which can be grouped under the following categories: Technological advancements and cross-sector applications; data infrastructure, AI models, and regulatory frameworks; workforce, education and societal factors; clinical efficiency and patient outcomes; trust, ethics, and AI adoption; financial pressures and industry investment in AI healthcare.
2024-12-19
Publications Office of the European Union
JRC140099
978-92-68-23026-8 (online),    978-92-68-23178-4 (print),   
1831-9424 (online),    1018-5593 (print),   
EUR 40161,    OP KJ-01-24-214-EN-N (online),    OP KJ-01-24-214-EN-C (print),   
https://publications.jrc.ec.europa.eu/repository/handle/JRC140099,   
10.2760/1426669 (online),    10.2760/0991947 (print),   
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