eHealth personalization in the next generation RPM systems

A. Tesanovic; G. Manev; M. Pechenizkiy; E. Vasilyeva

doi:10.1109/CBMS.2009.5255383

eHealth personalization in the next generation RPM systems

A. Tesanovic, G. Manev, M. Pechenizkiy, E. Vasilyeva

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Remote patient management (RPM) systems enable (i) monitoring of vital signs of patients at their home, and (ii) providing patients in their homes instructional, educational, or motivational feedback. As such, RPM systems collect a lot of (different types of) data about patients. Although richness of data provides an opportunity for tailoring and personalizing information services, there is a limited understanding of the necessary architecture, methodology, and tailoring criteria to facilitate personalization. In this paper we present (i) a possible next generation RPM system that enables personalization of educational content and its delivery to patients, (ii) introduce a generic methodology for personalization and emphasize the role of knowledge discovery (KDD) and (iii) outline the KDD process with a case study showing an example patient model and adaptation rules.

Originele taal-2	Engels
Titel	Proceedings 22nd IEEE International Symposium on Computer-Based Medical Systems (CMBS 2009, Albuquerque NM, USA, August 2-5, 2009)
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	1-8
ISBN van geprinte versie	978-1-4244-4879-1
DOI's	https://doi.org/10.1109/CBMS.2009.5255383
Status	Gepubliceerd - 2009

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title = "eHealth personalization in the next generation RPM systems",

abstract = "Remote patient management (RPM) systems enable (i) monitoring of vital signs of patients at their home, and (ii) providing patients in their homes instructional, educational, or motivational feedback. As such, RPM systems collect a lot of (different types of) data about patients. Although richness of data provides an opportunity for tailoring and personalizing information services, there is a limited understanding of the necessary architecture, methodology, and tailoring criteria to facilitate personalization. In this paper we present (i) a possible next generation RPM system that enables personalization of educational content and its delivery to patients, (ii) introduce a generic methodology for personalization and emphasize the role of knowledge discovery (KDD) and (iii) outline the KDD process with a case study showing an example patient model and adaptation rules.",

author = "A. Tesanovic and G. Manev and M. Pechenizkiy and E. Vasilyeva",

year = "2009",

doi = "10.1109/CBMS.2009.5255383",

language = "English",

isbn = "978-1-4244-4879-1",

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eHealth personalization in the next generation RPM systems. / Tesanovic, A.; Manev, G.; Pechenizkiy, M. et al.
Proceedings 22nd IEEE International Symposium on Computer-Based Medical Systems (CMBS 2009, Albuquerque NM, USA, August 2-5, 2009). Institute of Electrical and Electronics Engineers, 2009. blz. 1-8.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - eHealth personalization in the next generation RPM systems

AU - Tesanovic, A.

AU - Manev, G.

AU - Pechenizkiy, M.

AU - Vasilyeva, E.

PY - 2009

Y1 - 2009

N2 - Remote patient management (RPM) systems enable (i) monitoring of vital signs of patients at their home, and (ii) providing patients in their homes instructional, educational, or motivational feedback. As such, RPM systems collect a lot of (different types of) data about patients. Although richness of data provides an opportunity for tailoring and personalizing information services, there is a limited understanding of the necessary architecture, methodology, and tailoring criteria to facilitate personalization. In this paper we present (i) a possible next generation RPM system that enables personalization of educational content and its delivery to patients, (ii) introduce a generic methodology for personalization and emphasize the role of knowledge discovery (KDD) and (iii) outline the KDD process with a case study showing an example patient model and adaptation rules.

AB - Remote patient management (RPM) systems enable (i) monitoring of vital signs of patients at their home, and (ii) providing patients in their homes instructional, educational, or motivational feedback. As such, RPM systems collect a lot of (different types of) data about patients. Although richness of data provides an opportunity for tailoring and personalizing information services, there is a limited understanding of the necessary architecture, methodology, and tailoring criteria to facilitate personalization. In this paper we present (i) a possible next generation RPM system that enables personalization of educational content and its delivery to patients, (ii) introduce a generic methodology for personalization and emphasize the role of knowledge discovery (KDD) and (iii) outline the KDD process with a case study showing an example patient model and adaptation rules.

U2 - 10.1109/CBMS.2009.5255383

DO - 10.1109/CBMS.2009.5255383

M3 - Conference contribution

SN - 978-1-4244-4879-1

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BT - Proceedings 22nd IEEE International Symposium on Computer-Based Medical Systems (CMBS 2009, Albuquerque NM, USA, August 2-5, 2009)

PB - Institute of Electrical and Electronics Engineers

ER -

eHealth personalization in the next generation RPM systems

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