Evolution and challenges in the design of computational systems for triage assistance. Abad-Grau, M., M., Ierache, J., Cervino, C., & Sebastiani, P. Journal of biomedical informatics, 41(3):432-41, 6, 2008.
Evolution and challenges in the design of computational systems for triage assistance. [link]Website  abstract   bibtex   
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.
@article{
 title = {Evolution and challenges in the design of computational systems for triage assistance.},
 type = {article},
 year = {2008},
 identifiers = {[object Object]},
 keywords = {Artificial Intelligence,Decision Support Systems, Clinical,Decision Support Systems, Clinical: organization &,Software,Software Design,Triage,Triage: methods,Triage: organization & administration},
 pages = {432-41},
 volume = {41},
 websites = {http://www.sciencedirect.com/science/article/pii/S1532046408000130},
 month = {6},
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 abstract = {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.},
 bibtype = {article},
 author = {Abad-Grau, María M and Ierache, Jorge and Cervino, Claudio and Sebastiani, Paola},
 journal = {Journal of biomedical informatics},
 number = {3}
}

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