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. This is to be achieved by connecting citizens, authorities, civil society, first responders and creative practitioners to co-create inclusive, context-specific risk communication solutions that move beyond
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the emergency department. Trained on evidence accumulated in clinical settings and based on the patient’s particular clinical history, the CDSS will provide clinicians with personalized risk profiles for relevant
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current management is reactive (acting only after incidents emerge), PROSAFE-TWIN identifies high-risk segments in advance. It transforms the Safe System Approach into an operational reality, providing road
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history, the CDSS will provide clinicians with personalized risk profiles for relevant adverse outcomes, including self-harm, method escalation, suicide, premature mortality, as well as discontinuation
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strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics
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Post Doctoral Researcher Rinn Artificial Intelligence – Research & Innovation in Data Science and AI
patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics) • Multi-omics for non-cancer health screening applications, • Machine learning modelling
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stress conditions. Ultimately, PiTCROP aims to develop a practical, risk-based framework to support evidence-led decision-making on wastewater reuse in Irish agriculture, particularly in the context