Towards the second order adaptation in the next generation remote patient management systems

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

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Abstract

Remote Patient Management (RPM) systems are expected to be increasingly important for chronic disease management as they facilitate monitoring vital signs of patients at their home, alerting the care givers in case of worsening. They also provide patients with educational content. RPM systems collect a lot of (different types of) data about patients, providing an opportunity for personalizing information services. In our recent work we highlighted the importance of using available information for personalization and presented a possible next generation RPM system that enables personalization of educational content and its delivery to patients. We introduced a generic methodology for personalization and emphasized the role of knowledge discovery (KDD). In this paper we focus on the necessity of the second-order adaptation mechanisms in the RPM systems to address the challenge of continuous on-line (re)learning of actionable patterns from the patient data.
Original languageEnglish
Title of host publicationProceedings of the Workshop on Personalisation for eHealth (Pers4eHealth'09, Verona, Italy, July 19, 2009; co-located with AIME'09)
EditorsF. Grasso, C. Paris
Pages34-40
Publication statusPublished - 2009

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Information services
Data mining
Monitoring

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Tesanovic, A., Manev, G., Pechenizkiy, M., & Vasilyeva, E. (2009). Towards the second order adaptation in the next generation remote patient management systems. In F. Grasso, & C. Paris (Eds.), Proceedings of the Workshop on Personalisation for eHealth (Pers4eHealth'09, Verona, Italy, July 19, 2009; co-located with AIME'09) (pp. 34-40)
Tesanovic, A. ; Manev, G. ; Pechenizkiy, M. ; Vasilyeva, E. / Towards the second order adaptation in the next generation remote patient management systems. Proceedings of the Workshop on Personalisation for eHealth (Pers4eHealth'09, Verona, Italy, July 19, 2009; co-located with AIME'09). editor / F. Grasso ; C. Paris. 2009. pp. 34-40
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abstract = "Remote Patient Management (RPM) systems are expected to be increasingly important for chronic disease management as they facilitate monitoring vital signs of patients at their home, alerting the care givers in case of worsening. They also provide patients with educational content. RPM systems collect a lot of (different types of) data about patients, providing an opportunity for personalizing information services. In our recent work we highlighted the importance of using available information for personalization and presented a possible next generation RPM system that enables personalization of educational content and its delivery to patients. We introduced a generic methodology for personalization and emphasized the role of knowledge discovery (KDD). In this paper we focus on the necessity of the second-order adaptation mechanisms in the RPM systems to address the challenge of continuous on-line (re)learning of actionable patterns from the patient data.",
author = "A. Tesanovic and G. Manev and M. Pechenizkiy and E. Vasilyeva",
year = "2009",
language = "English",
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Tesanovic, A, Manev, G, Pechenizkiy, M & Vasilyeva, E 2009, Towards the second order adaptation in the next generation remote patient management systems. in F Grasso & C Paris (eds), Proceedings of the Workshop on Personalisation for eHealth (Pers4eHealth'09, Verona, Italy, July 19, 2009; co-located with AIME'09). pp. 34-40.

Towards the second order adaptation in the next generation remote patient management systems. / Tesanovic, A.; Manev, G.; Pechenizkiy, M.; Vasilyeva, E.

Proceedings of the Workshop on Personalisation for eHealth (Pers4eHealth'09, Verona, Italy, July 19, 2009; co-located with AIME'09). ed. / F. Grasso; C. Paris. 2009. p. 34-40.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Tesanovic A, Manev G, Pechenizkiy M, Vasilyeva E. Towards the second order adaptation in the next generation remote patient management systems. In Grasso F, Paris C, editors, Proceedings of the Workshop on Personalisation for eHealth (Pers4eHealth'09, Verona, Italy, July 19, 2009; co-located with AIME'09). 2009. p. 34-40