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Mining quantitative association rules in large relational tables
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Learning Bayesian networks from data: an information-theory based approach
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An empirical comparison of supervised learning algorithms
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A unified framework for image compression and segmentation by using an incremental neural network
Expert Systems with Applications: An International Journal
Breast cancer diagnosis using least square support vector machine
Digital Signal Processing
Towards efficient variables ordering for Bayesian networks classifier
Data & Knowledge Engineering
Artificial Intelligence in Medicine
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Journal of Biomedical Informatics
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Journal of Biomedical Informatics
Expert Systems with Applications: An International Journal
Detection of valvular heart disorders using wavelet packet decomposition and support vector machine
Expert Systems with Applications: An International Journal
Tabu Search-Enhanced Graphical Models for Classification in High Dimensions
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Expert Systems with Applications: An International Journal
Iterative bayesian network implementation by using annotated association rules
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Artificial Intelligence in Medicine
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Expert Systems with Applications: An International Journal
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Endovascular aneurysm repair (EVAR) is an advanced minimally invasive surgical technology that is helpful for reducing patients' recovery time, postoperative morbidity and mortality. This study proposes an ensemble model to predict postoperative morbidity after EVAR. The ensemble model was developed using a training set of consecutive patients who underwent EVAR between 2000 and 2009. All data required for prediction modeling, including patient demographics, preoperative, co-morbidities, and complication as outcome variables, was collected prospectively and entered into a clinical database. A discretization approach was used to categorize numerical values into informative feature space. Then, the Bayesian network (BN), artificial neural network (ANN), and support vector machine (SVM) were adopted as base models, and stacking combined multiple models. The research outcomes consisted of an ensemble model to predict postoperative morbidity after EVAR, the occurrence of postoperative complications prospectively recorded, and the causal effect knowledge by BNs with Markov blanket concept.