Neural networks as a tool to predict syncope risk in the Emergency Department
暂无分享,去创建一个
Raffaello Furlan | Nicola Montano | Greta Falavigna | Roberto Ippoliti | Giorgio Costantino | Matthew J Reed | R. Furlan | N. Montano | G. Costantino | G. Falavigna | R. Ippoliti | M. Reed | J. Quinn | A. Ungar | I. Casagranda | Benjamin C. Sun | Benjamin C Sun | James V Quinn | Shamai A Grossman | Monica Solbiati | M. Solbiati | Ivo Casagranda | Andrea Ungar | S. Grossman
[1] D. Morgan,et al. Unnecessary hospitalization and related harm for patients with low-risk syncope. , 2015, JAMA internal medicine.
[2] R. Furlan,et al. Is hospital admission valuable in managing syncope? Results from the STePS study. , 2014, Cardiology journal.
[3] C. Morillo,et al. Syncope clinical management in the emergency department: a consensus from the first international workshop on syncope risk stratification in the emergency department. , 2016, European heart journal.
[4] M. Brignole,et al. Clinical predictors of cardiac syncope at initial evaluation in patients referred urgently to a general hospital: the EGSYS score , 2008, Heart.
[5] C. Mangione,et al. External validation of the San Francisco Syncope Rule. , 2007, Annals of emergency medicine.
[6] R. Furlan,et al. Short- and long-term prognosis of syncope, risk factors, and role of hospital admission: results from the STePS (Short-Term Prognosis of Syncope) study. , 2008, Journal of the American College of Cardiology.
[7] I. Savelieva,et al. Syncope Unit: rationale and requirement--the European Heart Rhythm Association position statement endorsed by the Heart Rhythm Society. , 2015, 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.
[8] I. Stiell,et al. Priorities for emergency department syncope research. , 2014, Annals of emergency medicine.
[9] Benjamin C. Sun,et al. Standardized reporting guidelines for emergency department syncope risk-stratification research. , 2012, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.
[10] Kenneth Sands,et al. Predicting adverse outcomes in syncope. , 2007, The Journal of emergency medicine.
[11] E. Hess,et al. Outcomes in Canadian emergency department syncope patients--are we doing a good job? , 2013, The Journal of emergency medicine.
[12] George A Wells,et al. Derivation of the San Francisco Syncope Rule to predict patients with short-term serious outcomes. , 2004, Annals of emergency medicine.
[13] Massimo Santini,et al. Development and prospective validation of a risk stratification system for patients with syncope in the emergency department: the OESIL risk score. , 2003, European heart journal.
[14] R. L. Kennedy,et al. Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation. , 2005, Annals of emergency medicine.
[15] R. Furlan,et al. Syncope recurrence and mortality: a systematic review. , 2015, 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.
[16] R. Furlan,et al. Artificial Neural Networks and risk stratification models in Emergency Departments: The policy maker's perspective. , 2016, Health policy.
[17] J. Iwanicki,et al. The ROSE (Risk Stratification of Syncope in the Emergency Department) Study , 2010 .
[18] Patrick van der Smagt,et al. Introduction to neural networks , 1995, The Lancet.
[19] Greta Falavigna,et al. Financial ratings with scarce information: A neural network approach , 2012, Expert Syst. Appl..
[20] Cenker Eken,et al. Artificial neural network in predicting craniocervical junction injury: an alternative approach to trauma patients , 2008, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.
[21] R. Furlan,et al. Syncope risk stratification tools vs clinical judgment: an individual patient data meta-analysis. , 2014, The American journal of medicine.