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methodologies for assessing the robustness and safety of fully human-operated, AI-assisted human-operated and autonomous systems, considering risk assessment aligned with the EU AI Act, reliability and robustness
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.; This solution will be fundamental to ensuring greater robustness and reliability of data-centric applications (for example, databases and machine learning tools), as well as the durability of the data processed
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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