Explore the words cloud of the PEPPER project. It provides you a very rough idea of what is the project "PEPPER" about.
The following table provides information about the project.
Coordinator |
OXFORD BROOKES UNIVERSITY
Organization address contact info |
Coordinator Country | United Kingdom [UK] |
Project website | http://www.pepper.eu.com/ |
Total cost | 3˙548˙071 € |
EC max contribution | 3˙548˙071 € (100%) |
Programme |
1. H2020-EU.3.1.4. (Active ageing and self-management of health) |
Code Call | H2020-PHC-2015-single-stage |
Funding Scheme | RIA |
Starting year | 2016 |
Duration (year-month-day) | from 2016-02-01 to 2020-03-31 |
Take a look of project's partnership.
# | ||||
---|---|---|---|---|
1 | OXFORD BROOKES UNIVERSITY | UK (OXFORD) | coordinator | 643˙013.00 |
2 | IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE | UK (LONDON) | participant | 1˙198˙398.00 |
3 | FUNDACIO INSTITUT D'INVESTIGACIO BIOMEDICA DE GIRONA DOCTOR JOSEP TRUETA | ES (GIRONA) | participant | 651˙555.00 |
4 | CELLNOVO | UK (LONDON) | participant | 406˙248.00 |
5 | UNIVERSITAT DE GIRONA | ES (GIRONA) | participant | 327˙355.00 |
6 | ROMSOFT SRL | RO (IASI) | participant | 321˙500.00 |
This proposal is for a personalised decision support system for chronic disease management that will make predictions based on real-time data in order to empower individuals to participate in the self-management of their disease. The design will involve users at every stage to ensure that the system meets patient needs and raises clinical outcomes by preventing adverse episodes and improving lifestyle, monitoring and quality of life. Research will be conducted into the development of an innovative adaptive decision support system based on case-based reasoning combined with predictive computer modelling. The tool will offer bespoke advice for self-management by integrating personal health systems with broad and various sources of physiological, lifestyle, environmental and social data. The research will also examine the extent to which human behavioural factors and usability issues have previously hindered the wider adoption of personal guidance systems for chronic disease self-management. It will be developed and validated initially for people with diabetes on basal-bolus insulin therapy, but the underlying approach can be adapted to other chronic diseases. There will be a strong emphasis on safety, with glucose predictions, dose advice, alarms, limits and uncertainties communicated clearly to raise individual awareness of the risk of adverse events such as hypoglycaemia or hyperglycaemia. The outputs of this research will be validated in an ambulatory setting and a key aspect will be innovation management. All components will adhere to medical device standards in order to meet regulatory requirements and ensure interoperability, both with existing personal health systems and commercial products. The resulting architecture will improve interactions with healthcare professionals and provide a generic framework for providing adaptive mobile decision support, with innovation capacity to be applied to other applications, thereby increasing the impact of the project.
Ethical approval for the validation study | Other | 2020-01-20 17:38:59 |
Ethical approval for the feasibility study | Other | 2020-01-20 17:38:58 |
Clinical protocol for the clinical validation study | Other | 2020-01-20 17:38:58 |
Regulatory documentation | Documents, reports | 2020-01-20 17:38:58 |
Project website | Websites, patent fillings, videos etc. | 2020-01-20 17:38:58 |
Clinical protocol for feasibility study | Other | 2020-01-20 17:38:58 |
Report on standards and regulatory approval acceptance | Documents, reports | 2020-01-20 17:38:59 |
Take a look to the deliverables list in detail: detailed list of PEPPER deliverables.
year | authors and title | journal | last update |
---|---|---|---|
2017 |
Daniel Brown, Clare Martin, David Duce, Arantza Aldea, R. Harrison Towards a Formal Model of Type 1 Diabetes for Artificial Intelligence published pages: , ISSN: , DOI: |
Proceedings of the Second Workshop on Artificial Intelligence for Diabetes AIME 2017 | 2020-01-20 |
2016 |
Participants of the1st ECAI Workshop on Artificial intelligence for Diabetes 1st ECAI Workshop on Artificial intelligence for Diabetes published pages: , ISSN: , DOI: 10.5281/zenodo.400204 |
Proceedings of the 1st Workshop on Artificial Intelligence for Diabetes 1 | 2020-01-20 |
2017 |
Pau Herrero, Peter Pesl, Monika Reddy, Nick Oliver, Pantelis Georgiou Automatic Adjustment of Basal Insulin Infusion Rates in Type 1 Diabetes using Run-to-Run Control and Case-Based Reasoning published pages: , ISSN: , DOI: |
Proceedings of the Second Workshop on Artificial Intelligence for Diabetes AIME 2017 | 2020-01-20 |
2016 |
Herrero, Pau; López, Beatriz; Martin, Clare PEPPER: Patient Empowerment Through Predictive Personalised Decision Support published pages: , ISSN: , DOI: 10.5281/zenodo.427542 |
Proceedings of the 1st Workshop on Artificial Intelligence for Diabetes | 2020-01-20 |
2016 |
López Ibáñez, Beatriz; Viñas, Ramon; Torrent-Fontbona, Ferran; Fernández-Real Lemos, José Manuel Handling Missing Phenotype Data with Random Forests for Diabetes Risk Prognosis published pages: , ISSN: , DOI: 10.5281/zenodo.427979 |
Proceedings of the 1st Workshop on Artificial Intelligence for Diabetes 1 | 2020-01-20 |
2017 |
Torrent-Fontbona, Ferran; López Ibáñez, Beatriz; Pozo-Alonso, Alejandro A CBR-based bolus recommender system for type 1 diabetes published pages: , ISSN: , DOI: |
Proceedings of the Second Workshop on Artificial Intelligence for Diabetes 2 | 2020-01-20 |
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The information about "PEPPER" are provided by the European Opendata Portal: CORDIS opendata.