Suchergebnisse

Artificial intelligence (AI) has made impressive progress over the past few years, including many applications in medical imaging. Numerous commercial solutions based on AI techniques are now available for sale, forcing radiology practices to learn how to properly assess these tools. While several guidelines describing good practices for conducting and reporting AI-based research in medicine and radiology have been published, fewer efforts have focused on recommendations addressing the key questions to consider when critically assessing AI solutions before purchase. Commercial AI solutions are typically complicated software products, for the evaluation of which many factors are to be considered. In this work, authors from academia and industry have joined efforts to propose a practical framework that will help stakeholders evaluate commercial AI solutions in radiology (the ECLAIR guidelines) and reach an informed decision. Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services. KEY POINTS: • Numerous commercial solutions based on artificial intelligence techniques are now available for sale, and radiology practices have to learn how to properly assess these tools. • We propose a framework focusing on practical points to consider when assessing an AI solution in medical imaging, allowing all stakeholders to conduct relevant discussions with manufacturers and reach an informed decision as to whether to purchase an AI commercial solution for imaging applications. • Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services.

The potential scale of carbon dioxide capture and storage (CCS) under long-term decarbonisation scenarios means that analysis on the contribution of large international CO2 storage reservoirs is critical. This paper compares the potentially key role of CCS within cost-optimizing energy systems modelling at the national level (ensuring country-specific technical, economic and policy detail), and the regional level (ensuring transboundary electricity and CO2 trade). Analysis at alternate model scales investigates the full range of drivers on the feasibility and trade-offs in using the Utsira formation as a common North Sea CO2 storage resource. A robust finding is that low carbon electricity is a primary decarbonisation pathway and that CCS plays a key role (32–40%) within this portfolio. This paper confirms that the overall driver of the amount of CCS utilized is the climate policy, with by 2050 a total of 475–570 MtCO2 captured and stored (of which 110–120 MtCO2 is stored in Utsira) under an 80% CO2 reduction target. Modelled country differences are much larger due to specific national policies and to regional (EU) commodity trading. From 2030 onwards, Utsira plays a key role within the CO2 storage cost curve, with the Netherlands and the UK being the largest contributors, followed by transboundary flows of CO2 from other countries. However, overall regional CCS flows may be larger (for example under low fossil fuel prices) than the estimated (and uncertain) maximum annual injection rates into Utsira which could potentially represent a significant constraint.