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   <dc:title>Personalised Clinical Decision Support For Diabetes Management Using Real-time Data [Pòster]</dc:title>
   <dc:creator>Martin, Clare</dc:creator>
   <dc:creator>Aldea, Arantza</dc:creator>
   <dc:creator>Brown, Daniel</dc:creator>
   <dc:creator>Duce, David</dc:creator>
   <dc:creator>Fernández-Real Lemos, José Manuel</dc:creator>
   <dc:creator>Gay Sacristán, Pablo</dc:creator>
   <dc:creator>Georgiou, Pantelis</dc:creator>
   <dc:creator>Harrison, R.</dc:creator>
   <dc:creator>Herrero i Viñas, Pau</dc:creator>
   <dc:creator>Innocenti, Bianca</dc:creator>
   <dc:creator>López Ibáñez, Beatriz</dc:creator>
   <dc:creator>Leal Moncada, Yenny Teresa</dc:creator>
   <dc:creator>Nita, Lucian</dc:creator>
   <dc:creator>Pesl, Peter</dc:creator>
   <dc:creator>Petite, Roberto</dc:creator>
   <dc:creator>Reddy, Monika</dc:creator>
   <dc:creator>Shapley, Julian</dc:creator>
   <dc:creator>Torrent-Fontbona, Ferran</dc:creator>
   <dc:creator>Waite, Marion</dc:creator>
   <dc:creator>Wos, Marzena</dc:creator>
   <dc:creator>Oliver, Nick</dc:creator>
   <dc:subject>Raonament basat en casos -- Congressos</dc:subject>
   <dc:subject>Case-based reasoning -- Congresses</dc:subject>
   <dc:subject>Diabetis -- Congressos</dc:subject>
   <dc:subject>Diabetes -- Congresses</dc:subject>
   <dc:subject>Intel·ligència artificial -- Aplicacions a la medicina -- Congressos</dc:subject>
   <dc:subject>Artificial intelligence -- Medical applications -- Congresses</dc:subject>
   <dc:subject>Sistemes d'ajuda a la decisió -- Congressos</dc:subject>
   <dc:subject>Decision support systems -- Congresses</dc:subject>
   <dcterms:abstract>Pòster de congrés presentat a: International Conference on Advanced Technologies &amp; Treatments for Diabetes (ATTD) (10th: 15-18 Febrer 2017: Berlin)</dcterms:abstract>
   <dcterms:abstract>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</dcterms:abstract>
   <dcterms:abstract>This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689810</dcterms:abstract>
   <dcterms:dateAccepted>2024-06-13T09:51:22Z</dcterms:dateAccepted>
   <dcterms:available>2024-06-13T09:51:22Z</dcterms:available>
   <dcterms:created>2024-06-13T09:51:22Z</dcterms:created>
   <dcterms:issued>2017</dcterms:issued>
   <dc:type>info:eu-repo/semantics/conferenceObject</dc:type>
   <dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
   <dc:identifier>http://hdl.handle.net/10256/17707</dc:identifier>
   <dc:relation>info:eu-repo/semantics/altIdentifier/doi/10.5281/zenodo.820449</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/EC/H2020/689810/EU/Patient Empowerment through Predictive PERsonalised decision support/PEPPER</dc:relation>
   <dc:rights>Tots els drets reservats</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:publisher>PEPPER (Patient Empowerment through Predictive PERsonalised decision support)</dc:publisher>
   <dc:source>Articles publicats (D-EEEiA)</dc:source>
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