Abstract
| Original language | Undefined |
|---|---|
| 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
- EWI-26693
- Internet of Things
- EHealth
- Knowledge based systems
- IR-99029
- METIS-315161
- Clinical guidelines
- Business Process Modelling
- Body Area Networks
- Evidence-based medicine
- Distributed systems
- Clinical Decision Support
Cite this
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The conceptual MADE framework for pervasive and knowledge-based decision support in telemedicine. / Fung, L.S.N.; Jones, Valerie M.; Widya, I.A.; Broens, T.H.F.; Larburu Rubio, Nekane; Bults, Richard G.A.; Shalom, Erez; Hermens, Hermanus J.
In: International journal of knowledge and systems science, Vol. 7, No. 1, 2016, p. 25-39.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - The conceptual MADE framework for pervasive and knowledge-based decision support in telemedicine
AU - Fung, L.S.N.
AU - Jones, Valerie M.
AU - Widya, I.A.
AU - Broens, T.H.F.
AU - Larburu Rubio, Nekane
AU - Bults, Richard G.A.
AU - Shalom, Erez
AU - Hermens, Hermanus J.
N1 - eemcs-eprint-26693
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - BSS-Technology supported cognitive training
KW - EWI-26693
KW - Internet of Things
KW - EHealth
KW - Knowledge based systems
KW - IR-99029
KW - METIS-315161
KW - Clinical guidelines
KW - Business Process Modelling
KW - Body Area Networks
KW - Evidence-based medicine
KW - Distributed systems
KW - Clinical Decision Support
U2 - 10.4018/IJKSS.2016010102
DO - 10.4018/IJKSS.2016010102
M3 - Article
VL - 7
SP - 25
EP - 39
JO - International journal of knowledge and systems science
JF - International journal of knowledge and systems science
SN - 1947-8208
IS - 1
ER -