Probabilistic reasoning in expert systems: theory and algorithms
Probabilistic reasoning in expert systems: theory and algorithms
A Bayesian method for constructing Bayesian belief networks from databases
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Machine Learning - Special issue on learning with probabilistic representations
Expert Systems and Probabiistic Network Models
Expert Systems and Probabiistic Network Models
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Readings in Machine Learning
Integration Mechanisms and Hospital Efficiency in Integrated Health Care Delivery Systems
Journal of Medical Systems
Incremental Induction of Decision Trees
Machine Learning
Profiling your customers using Bayesian networks
ACM SIGKDD Explorations Newsletter
On Development and Evaluation of Prototype Mobile Decision Support for Hospital Triage
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 6 - Volume 06
A Mobile Emergency Triage Decision Support System Evaluation
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 05
Belief Update in Bayesian Networks Using Uncertain Evidence
ICTAI '06 Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence
Methodological Review: Data integration and genomic medicine
Journal of Biomedical Informatics
A model of inductive bias learning
Journal of Artificial Intelligence Research
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
A study of cross-validation and bootstrap for accuracy estimation and model selection
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Sequential update of Bayesian network structure
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Diagnosis of chronic idiopathic inflammatory bowel disease using bayesian networks
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Paper: Modeling by shortest data description
Automatica (Journal of IFAC)
Guest Editorial: Computer-based decision support for critical and emergency care
Journal of Biomedical Informatics
Artificial Intelligence in Medicine
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Compared with expert systems for specific disease diagnosis, knowledge-based systems to assist decision making in triage usually try to cover a much wider domain but can use a smaller set of variables due to time restrictions, many of them subjective so that accurate models are difficult to build. In this paper, we first study criteria that most affect the performance of systems for triage assistance. Such criteria include whether principled approaches from machine learning can be used to increase accuracy and robustness and to represent uncertainty, whether data and model integration can be performed or whether temporal evolution can be modeled to implement retriage or represent medication responses. Following the most important criteria, we explore current systems and identify some missing features that, if added, may yield to more accurate triage systems.