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

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: Contribution to journal › Conference paper › peer-review

1 Citation (Scopus)

Abstract

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 language	English
Pages (from-to)	60-67
Number of pages	8
Journal	CEUR Workshop Proceedings
Volume	2429
Publication status	Published - 1 Jan 2019
Event	4th International Workshop on Knowledge Discovery in Healthcare Data, KDH 2019 - Macao, China Duration: 10 Aug 2019 → 16 Aug 2019

Cite this

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title = "Learning to self-manage by intelligent monitoring, prediction and intervention",

abstract = "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.",

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

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TY - JOUR

T1 - Learning to self-manage by intelligent monitoring, prediction and intervention

AU - Wiratunga, Nirmalie

AU - Corsar, David

AU - Martin, Kyle

AU - Wijekoon, Anjana

AU - Elyan, Eyad

AU - Cooper, Kay

AU - Ibrahim, Zina

AU - Celiktutan, Oya

AU - Dobson, Richard J.

AU - McKenna, Stephen

AU - Morris, Jacqui

AU - Waller, Annalu

AU - Abd-Alhammed, Raed

AU - Qahwaji, Rami

AU - Chaudhuri, Ray

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

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M3 - Conference paper

AN - SCOPUS:85071683320

SN - 1613-0073

VL - 2429

SP - 60

EP - 67

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 4th International Workshop on Knowledge Discovery in Healthcare Data, KDH 2019

Y2 - 10 August 2019 through 16 August 2019

ER -

Learning to self-manage by intelligent monitoring, prediction and intervention

Abstract

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