Context-Aware Knowledge Modelling for Decision Support in E-Health

Citation:
Anya, O., H. Tawfik, S. Amin, A. Nagar, and K. Shaalan, "Context-Aware Knowledge Modelling for Decision Support in E-Health", In the Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), Barcelona, Spain, IEEE, 21 July, 2010. copy at www.tinyurl.com/zx64pdy

Date Presented:

21 July

Abstract:

In the context of e-health, professionals and healthcare service providers in various organisational and geographical locations are to work together, using information and communication systems, for the purpose of providing better patient-centred and technology-supported healthcare services at any time and from anywhere. However, various organisations and geographies have varying contexts of work, which are dependent on their local work culture, available expertise,available technologies, people's perspectives and attitudes and organisational and regional agendas. As a result, there is the need to ensure that a suggestion – information and knowledge –provided by a professional to support decision making in a different, and often distant, organisation and geography takes into cognizance the context of the local work setting in which the suggestion is to be used. To meet this challenge, we propose a framework for context-aware knowledge modelling in e-health,which we refer to as Context Morph. Context Morph combines the commonKADS knowledge modelling methodology with the concept of activity landscape and context-aware modelling techniques in order to morph, i.e. enrich and optimise, a knowledge resource to support decision making across various contexts of work. The goal is to integrate explicit information and tacit expert experiences across various work domains into a knowledge resource adequate for supporting the operational context of the work setting in which it is to be used.

Notes:

n/a

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