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

Pòster de congrés presentat a: International Conference on Advanced Technologies & Treatments for Diabetes (ATTD) (10th: 15-18 Febrer 2017: Berlin)

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

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689810

PEPPER (Patient Empowerment through Predictive PERsonalised decision support)

Author: Martin, Clare
Aldea, Arantza
Brown, Daniel
Duce, David
Fernández-Real Lemos, José Manuel
Gay Sacristán, Pablo
Georgiou, Pantelis
Harrison, R.
Herrero i Viñas, Pau
Innocenti, Bianca
López Ibáñez, Beatriz
Leal Moncada, Yenny Teresa
Nita, Lucian
Pesl, Peter
Petite, Roberto
Reddy, Monika
Shapley, Julian
Torrent-Fontbona, Ferran
Waite, Marion
Wos, Marzena
Oliver, Nick
Date: 2017
Abstract: Pòster de congrés presentat a: International Conference on Advanced Technologies & Treatments for Diabetes (ATTD) (10th: 15-18 Febrer 2017: Berlin)
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
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689810
Format: application/pdf
Document access: http://hdl.handle.net/10256/17707
Language: eng
Publisher: PEPPER (Patient Empowerment through Predictive PERsonalised decision support)
Collection: info:eu-repo/semantics/altIdentifier/doi/10.5281/zenodo.820449
info:eu-repo/grantAgreement/EC/H2020/689810
Rights: Tots els drets reservats
Subject: Raonament basat en casos -- Congressos
Case-based reasoning -- Congresses
Diabetis -- Congressos
Diabetes -- Congresses
Intel·ligència artificial -- Aplicacions a la medicina -- Congressos
Artificial intelligence -- Medical applications -- Congresses
Sistemes d’ajuda a la decisió -- Congressos
Decision support systems -- Congresses
Title: Personalised Clinical Decision Support For Diabetes Management Using Real-time Data [Pòster]
Type: info:eu-repo/semantics/conferenceObject
Repository: DUGiDocs

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