Learning to Self-Manage by Intelligent Monitoring, Prediction and Intervention

Nirmalie Wiratunga, David Corsar, Kyle Martin, Anjana Wijekoon, Eyad Elyan, Kay Cooper, Zina Ibrahim, Oya Celiktutan, Richard J. Dobson, Stephen McKenna, Jacqui Morris, Annalu Waller, Raed Abd-Alhammed, Rami Qahwaji, Ray Chaudhuri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
46 Downloads (Pure)


Despite the growing prevalence of multimorbidities, current digital self-management approaches still prioritise single conditions. The future of outof-hospital care requires researchers to expand their horizons; integrated assistive technologies should enable people to live their life well regardless of their chronic conditions. Yet, many of the current digital self-management technologies are not equipped to handle this problem. In this position paper, we suggest the solution for these issues is a model-aware and data agnostic platform formed on the basis of a tailored self-management plan and three integral concepts - Monitoring (M) multiple information sources to empower Predictions (P) and trigger intelligent Interventions (I). Here we present our ideas for the formation of such a platform, and its potential impact on quality of life for sufferers of chronic conditions.
Original languageEnglish
Title of host publicationKDH 2019
Subtitle of host publicationProceedings of the 4th International Workshop on Knowledge Discovery in Healthcare Data
EditorsNirmalie Wiratunga, Frans Coenen, Sadiq Sani
Place of PublicationGermany
Number of pages8
Publication statusPublished - 2019
EventIJCAI-19: 28th International Joint Conference on Artificial Intelligence - Macao, China
Duration: 10 Aug 201916 Aug 2019

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


Internet address

ASJC Scopus subject areas

  • General Computer Science


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