DUGiDocsPersonalised Clinical Decision Support For Diabetes Management Using Real-time Data [Pòster]
dc.contributor.author
dc.date.accessioned
2020-02-10T11:55:19Z
dc.date.available
2020-02-10T11:55:19Z
dc.date.issued
2017
dc.identifier.uri
dc.description
Pòster de congrés presentat a: International Conference on Advanced Technologies & Treatments for Diabetes (ATTD) (10th: 15-18 Febrer 2017: Berlin)
dc.description.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
dc.description.sponsorship
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 689810
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
PEPPER (Patient Empowerment through Predictive PERsonalised decision support)
dc.relation.ispartofseries
Articles publicats (D-EEEiA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Personalised Clinical Decision Support For Diabetes Management Using Real-time Data [Pòster]
dc.type
info:eu-repo/semantics/conferenceObject
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.relation.projectID
info:eu-repo/grantAgreement/EC/H2020/689810/EU/Patient Empowerment through Predictive PERsonalised decision support/PEPPER
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.relation.FundingProgramme
dc.relation.ProjectAcronym