Quality assessment of hemodialysis services through temporal data mining

Riccardo Bellazzi, Cristiana Larizza, Paolo Magni, Roberto Bellazzi

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

6 Citations (Scopus)

Abstract

This paper describes a research project that deals with the definition of methods and tools for the assessment of the clinical performance of a hemodialysis service on the basis of time series data automatically collected during the monitoring of hemodialysis sessions. While simple statistical summaries are computed to assess basic outcomes, Intelligent Data Analysis and Temporal Data mining techniques are applied to gain insight and to discover knowledge on the causes of unsatisfactory clinical results. In particular, different techniques, comprising multi-scale filtering, Temporal Abstractions, association rules discovery and subgroup discovery are applied on the time series. The paper describes the application domain, the basic goals of the project and the methodological approach applied for time series data analysis. The current results of the project, obtained on the data coming from more than 2500 dialysis sessions of 33 patients monitored for seven months, are also shown.

Original languageEnglish
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
EditorsM. Dojat, E. Keravnou, P. Barahona
Pages11-20
Number of pages10
Volume2780
Publication statusPublished - 2003
Event9th Conference on Atificial Intelligence in Medicine in Europe, AIME 2003 - Protaras, Greece
Duration: Oct 18 2003Oct 22 2003

Other

Other9th Conference on Atificial Intelligence in Medicine in Europe, AIME 2003
CountryGreece
CityProtaras
Period10/18/0310/22/03

Fingerprint

Quality Assessment
Time Series Data
Data mining
Time series
Data analysis
Data Mining
Association Rules
Dialysis
Filtering
Association rules
Subgroup
Monitoring
Abstraction
Knowledge

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Science(all)
  • Theoretical Computer Science
  • Engineering(all)

Cite this

Bellazzi, R., Larizza, C., Magni, P., & Bellazzi, R. (2003). Quality assessment of hemodialysis services through temporal data mining. In M. Dojat, E. Keravnou, & P. Barahona (Eds.), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 2780, pp. 11-20)

Quality assessment of hemodialysis services through temporal data mining. / Bellazzi, Riccardo; Larizza, Cristiana; Magni, Paolo; Bellazzi, Roberto.

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). ed. / M. Dojat; E. Keravnou; P. Barahona. Vol. 2780 2003. p. 11-20.

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

Bellazzi, R, Larizza, C, Magni, P & Bellazzi, R 2003, Quality assessment of hemodialysis services through temporal data mining. in M Dojat, E Keravnou & P Barahona (eds), Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). vol. 2780, pp. 11-20, 9th Conference on Atificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Greece, 10/18/03.
Bellazzi R, Larizza C, Magni P, Bellazzi R. Quality assessment of hemodialysis services through temporal data mining. In Dojat M, Keravnou E, Barahona P, editors, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Vol. 2780. 2003. p. 11-20
Bellazzi, Riccardo ; Larizza, Cristiana ; Magni, Paolo ; Bellazzi, Roberto. / Quality assessment of hemodialysis services through temporal data mining. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). editor / M. Dojat ; E. Keravnou ; P. Barahona. Vol. 2780 2003. pp. 11-20
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