Interpreting longitudinal data through temporal abstractions: An application to diabetic patients monitoring

Riccardo Bellazzi, Cristiana Larizza, Alberto Riva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we present a new approach for the intelligent analysis of longitudinal data coming from diabetic patients home monitoring. This approach consists in exploiting temporal abstractions to preprocess the raw data and to obtain a new time series of abstract episodes, whose features are then interpreted through statistical and probabilistic techniques. We finally show the application of this methodology on the data of two diabetic patients monitored for six months.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages287-298
Number of pages12
Volume1280
ISBN (Print)9783540633464
Publication statusPublished - 1997
Event2nd International Symposium on Intelligent Data Analysis, IDA 1997 - London, United Kingdom
Duration: Aug 4 1997Aug 6 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1280
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Symposium on Intelligent Data Analysis, IDA 1997
CountryUnited Kingdom
CityLondon
Period8/4/978/6/97

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Bellazzi, R., Larizza, C., & Riva, A. (1997). Interpreting longitudinal data through temporal abstractions: An application to diabetic patients monitoring. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1280, pp. 287-298). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1280). Springer Verlag.