In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

Heart Failure analysis Dashboard for patient's remote monitoring combining multiple artificial intelligence technologies / G. Guidi; M. C. Pettenati; R. Miniati; E. Iadanza. - ELETTRONICO. - 2012:(2012), pp. 2210-2213. (Intervento presentato al convegno 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 tenutosi a San Diego, California USA nel 28 August - 1 September, 2012) [10.1109/EMBC.2012.6346401].

Heart Failure analysis Dashboard for patient's remote monitoring combining multiple artificial intelligence technologies

GUIDI, GABRIELE;MINIATI, ROBERTO;IADANZA, ERNESTO
2012

Abstract

In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.
2012
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
San Diego, California USA
28 August - 1 September, 2012
G. Guidi; M. C. Pettenati; R. Miniati; E. Iadanza
File in questo prodotto:
File Dimensione Formato  
EMBC12_0668_FI.pdf

Accesso chiuso

Descrizione: Articolo principale
Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: Tutti i diritti riservati
Dimensione 452.62 kB
Formato Adobe PDF
452.62 kB Adobe PDF   Richiedi una copia
EMBC12_0668_MS.pdf

Accesso chiuso

Dimensione 530.71 kB
Formato Unknown
530.71 kB Unknown   Richiedi una copia

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

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/919965
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 28
  • ???jsp.display-item.citation.isi??? 22
social impact