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Inferencing Strategies for Automated ALERTS on Critically Abnormal Laboratory and Blood Gas Data
Automating the recognition of critically abnormal laboratory and blood gas results is a non-trivial task. Human judgement is remarkably multifactorial with regard to evaluation of incoming data and appreciation of seriously abnormal events. We have implemented a decision support module for a compreh...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
1989
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2245759/ |
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