There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying the risk in this patient group.

Neural networks as a tool to predict syncope risk in the Emergency Department / Costantino, Giorgio; Falavigna, Greta; Solbiati, Monica; Casagranda, Ivo; Sun, Benjamin C; Grossman, Shamai A; Quinn, James V; Reed, Matthew J; Ungar, Andrea; Montano, Nicola; Furlan, Raffaello; Ippoliti, Roberto. - In: EUROPACE. - ISSN 1099-5129. - STAMPA. - 19:(2017), pp. 1891-1895. [10.1093/europace/euw336]

Neural networks as a tool to predict syncope risk in the Emergency Department

Ungar, Andrea;
2017

Abstract

There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying the risk in this patient group.
2017
19
1891
1895
Goal 3: Good health and well-being for people
Costantino, Giorgio; Falavigna, Greta; Solbiati, Monica; Casagranda, Ivo; Sun, Benjamin C; Grossman, Shamai A; Quinn, James V; Reed, Matthew J; Ungar, Andrea; Montano, Nicola; Furlan, Raffaello; Ippoliti, Roberto
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1102735
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