The Strength of Weak Learnability
Machine Learning
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
C4.5: programs for machine learning
C4.5: programs for machine learning
Boosting a weak learning algorithm by majority
Information and Computation
Machine Learning
Estimating drug/plasma concentration levels by applying neural networks to pharmacokinetic data sets
Decision Support Systems
Ensembling neural networks: many could be better than all
Artificial Intelligence
Advances in Feedforward Neural Networks: Demystifying Knowledge Acquiring Black Boxes
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Backpropagation neural nets with one and two hidden layers
IEEE Transactions on Neural Networks
A framework for supporting emergency messages in wireless patient monitoring
Decision Support Systems
Enabling ubiquitous patient monitoring: Model, decision protocols, opportunities and challenges
Decision Support Systems
A Personal Assistant for Autonomous Life
HCD 09 Proceedings of the 1st International Conference on Human Centered Design: Held as Part of HCI International 2009
An investigation of neural network classifiers with unequal misclassification costs and group sizes
Decision Support Systems
An ANFIS-based model for predicting adequacy of vancomycin regimen using improved genetic algorithm
Expert Systems with Applications: An International Journal
A text-based decision support system for financial sequence prediction
Decision Support Systems
Nearest-neighbor-based approach to time-series classification
Decision Support Systems
A framework for enabling patient monitoring via mobile ad hoc network
Decision Support Systems
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Clinicians' drug regimen decision making is critical, particularly when involving high-alert medications. In this study, we use decision-tree induction C4.5 and a backpropagation neural network to construct decision support systems for predicting the regimen adequacy of vancomycin, a glycopeptide antimicrobial antibiotic effective for Gram-positive bacterial infections. We comparatively evaluate the respective systems using a total of 987 clinical vancomycin cases collected from a major tertiary medical center in southern Taiwan. We supplement each system using Bagging and then examine the predictive power of the extended system. Overall, our evaluation results show the overall accuracy of the decision support system based on C4.5 or the neural network to be significantly higher than that of the benchmark one-compartment pharmacokinetic model. Use of Bagging can considerably improve the effectiveness of each system across different performance measures, particularly for cases of decision classes in which the base systems (i.e., without Bagging) perform modestly. Taken together, our evaluation results seem to favor the use of Bagging to enhance the performance of decision support systems constructed using decision-tree induction C4.5.