Abstract
Telemedicine systems are inherently distributed, but, especially in the context of the Internet-of-Things, their complete physical configuration may only be determined after design time by considering, for example, the individual patient's needs. Therefore, to enable pervasive and knowledge-based decision support to be provided in telemedicine, a conceptual framework was developed for modelling and executing clinical knowledge as networks of four types of concurrent processes: Monitoring (M), Analysis (A), Decision (D) and Effectuation (E). In this way, the required decision support functionality can, as presented in this article, be distributed at run-time by mapping different portions of the knowledge across the devices constituting the system. This MADE framework was applied to model a clinical guideline for gestational diabetes mellitus and to derive a prototype knowledge-based system that executes the resulting MADE network. Thus it is shown to support the full development trajectory of a telemedicine system, including analysis, design and implementation.
Original language | English |
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Pages (from-to) | 25-39 |
Number of pages | 15 |
Journal | International journal of knowledge and systems science |
Volume | 7 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2016 |
Keywords
- BSS-Technology supported cognitive training
- Internet of Things (IoT)
- EHealth
- Knowledge based systems
- Clinical guidelines
- Business Process Modelling
- Body Area Networks
- Evidence-based medicine
- Distributed systems
- Clinical Decision Support