Neural networks as a tool to predict syncope risk in the Emergency Department.
Journal:
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
PMID:
28017935
Abstract
AIMS: 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.
Authors
Keywords
Adult
Aged
Aged, 80 and over
Area Under Curve
Cardiology Service, Hospital
Clinical Decision-Making
Databases, Factual
Decision Support Techniques
Electrocardiography
Emergency Service, Hospital
Female
Humans
Italy
Male
Middle Aged
Neural Networks, Computer
Predictive Value of Tests
Prognosis
Reproducibility of Results
Risk Assessment
Risk Factors
ROC Curve
Syncope
Time Factors
Triage