Poster Open Access

Personalised Clinical Decision Support For Diabetes Management Using Real-time Data

Martin, Clare; Aldea, Arantza; Brown, Daniel; Fernández-Real, Jose Manuel; Gay, Pablo; Georgiou, Pantelis; Harrison, R.; Herrero, Pau; Innocenti, Bianca; López, Beatriz; Leal, Yenny; Nita, Lucian; Pesl, Peter; Petite, Roberto; Reddy, Monika; Torrent-Fontbona, Ferran; Waite, Marion; Wos, Marzena; Oliver, Nicholas; Shapley, Julian

PEPPER (Patient Empowerment through Predictive PERsonalised decision support) is an EU-funded research project to develop a personalised clinical decision support system for Type 1 diabetes self-management. The tool provides insulin bolus dose advice and carbohydrate recommendations, tailored to the needs of individuals. The former is determined by Case-Based Reasoning (CBR), an artificial intelligence technique that adapts to new situations according to past experience. The latter uses a predictive computer model that also promotes safety by providing glucose alarms, low-glucose insulin suspension and fault detection.

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