Prediction of in-hospital mortality after ruptured abdominal aortic aneurysm repair using an artificial neural network.
Journal:
Journal of vascular surgery
PMID:
25953014
Abstract
OBJECTIVE: Ruptured abdominal aortic aneurysm (rAAA) carries a high mortality rate, even with prompt transfer to a medical center. An artificial neural network (ANN) is a computational model that improves predictive ability through pattern recognition while continually adapting to new input data. The goal of this study was to effectively use ANN modeling to provide vascular surgeons a discriminant adjunct to assess the likelihood of in-hospital mortality on a pending rAAA admission using easily obtainable patient information from the field.
Authors
Keywords
Age Factors
Aged
Aged, 80 and over
Algorithms
Aortic Aneurysm, Abdominal
Aortic Rupture
Area Under Curve
Blood Vessel Prosthesis Implantation
Databases, Factual
Decision Support Techniques
Endovascular Procedures
Female
Heart Arrest
Hospital Mortality
Humans
Logistic Models
Male
Middle Aged
Multivariate Analysis
Neural Networks, Computer
Odds Ratio
Predictive Value of Tests
Retrospective Studies
Risk Assessment
Risk Factors
ROC Curve
Shock
Tennessee
Time Factors
Treatment Outcome
Unconsciousness