Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences
Joint Authors
Baker, Andrew
Levine, Mitchell A. H.
Lo, Benjamin W. Y.
Macdonald, R. Loch
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-10
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Objective.
The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH).
Methods.
The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients).
Results.
Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs).
Similar trends were noted in Bayesian and linear regression ORs.
Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure.
Heteroscedasticity was present in the nontransformed dataset.
Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model.
Fuzzy logic decision rules (centroid defuzzification technique) denoted cut-off points for poor prognosis at greater than 2.5 clusters.
Discussion.
This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication.
American Psychological Association (APA)
Lo, Benjamin W. Y.& Macdonald, R. Loch& Baker, Andrew& Levine, Mitchell A. H.. 2013. Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-506873
Modern Language Association (MLA)
Lo, Benjamin W. Y.…[et al.]. Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-506873
American Medical Association (AMA)
Lo, Benjamin W. Y.& Macdonald, R. Loch& Baker, Andrew& Levine, Mitchell A. H.. Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-506873
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-506873