In this article we present a new approach for the intelligent analysis of longitudinal data coming from chronic patients home monitoring. This approach exploits temporal abstractions to pre-process the raw data and to obtain a new time series of abstract episodes, whose features are then interpreted through statistical and probabilistic techniques. We describe in detail an application of the presented technique to the analysis of diabetic patients' data, showing some results obtained on a real case monitored for six months.

Temporal abstractions for interpreting chronic patients monitoring data

BELLAZZI, RICCARDO;LARIZZA, CRISTIANA;
1998-01-01

Abstract

In this article we present a new approach for the intelligent analysis of longitudinal data coming from chronic patients home monitoring. This approach exploits temporal abstractions to pre-process the raw data and to obtain a new time series of abstract episodes, whose features are then interpreted through statistical and probabilistic techniques. We describe in detail an application of the presented technique to the analysis of diabetic patients' data, showing some results obtained on a real case monitored for six months.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/100522
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 69
  • ???jsp.display-item.citation.isi??? ND
social impact