The purpose of this study is the evaluation of the web cloud-based analytic service IBM Watson Analytics as a tool for the management of Congestive Heart Failure (CHF). In particular, we want to assess if this service is suitable for the identification of physiological parameters able to predict outputs of interest such as disease severity, among a set of various physiological parameters and the realization of a predictive model. Using IBM Watson Analytics, we analyzed a database consisting of 250 records containing physiological parameters from 250 patients suffering from Congestive Heart Failure. Among the physiological parameters, we identified the best predictors of 2 outputs of interest (Severity of Congestive Heart Failure and Exacerbation Frequency) and analyzed the relationship between outputs and predictors and between predictors and the other physiological parameters.

IBM Watson Analytics for Managing Congestive Heart Failure / Mudura, Vlad Antoniu; Frosini, Francesco; Iadanza, Ernesto. - STAMPA. - 65:(2017), pp. 1025-1028. (Intervento presentato al convegno European Medical and Biological Engineering' and 'Nordic-Baltic Biomedical Engineering) [10.1007/978-981-10-5122-7_256].

IBM Watson Analytics for Managing Congestive Heart Failure

MUDURA, VLAD ANTONIU;FROSINI, FRANCESCO;IADANZA, ERNESTO
2017

Abstract

The purpose of this study is the evaluation of the web cloud-based analytic service IBM Watson Analytics as a tool for the management of Congestive Heart Failure (CHF). In particular, we want to assess if this service is suitable for the identification of physiological parameters able to predict outputs of interest such as disease severity, among a set of various physiological parameters and the realization of a predictive model. Using IBM Watson Analytics, we analyzed a database consisting of 250 records containing physiological parameters from 250 patients suffering from Congestive Heart Failure. Among the physiological parameters, we identified the best predictors of 2 outputs of interest (Severity of Congestive Heart Failure and Exacerbation Frequency) and analyzed the relationship between outputs and predictors and between predictors and the other physiological parameters.
2017
IFMBE Proceedings
European Medical and Biological Engineering' and 'Nordic-Baltic Biomedical Engineering
Mudura, Vlad Antoniu; Frosini, Francesco; Iadanza, Ernesto
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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/2158/1090053
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact