基于问题提示清单和个人决策指导的急性阑尾炎患儿决策辅助干预

目的 探讨基于问题提示清单和个人决策指导的决策辅助干预在急性阑尾炎患儿治疗决策中的应用效果。方法 便利选取急性阑尾炎患儿监护人为研究对象,按照患儿就诊时间分为对照组和干预组各49人。对照组实施常规术前谈话和健康教育,干预组在对照组基础上实施基于问题提示清单和个人决策指导的决策辅助干预。比较两组决策困境、决策准备度和决策参与满意度。结果 干预后,干预组患儿监护人决策困境总分显著低于对照组,决策准备度及决策参与满意度总分显著高于对照组(均P<0.05)。结论 基于问题提示清单和个人决策指导的决策辅助干预,能够降低急性阑尾炎患儿监护人决策困境,提高其决策准备度和决策参与满意度。

Improving the Collocation Extraction Method Using an Untagged Corpus for Persian Word Sense Disambiguation

Word sense disambiguation is used in many natural language processing fields. One of the ways of disambiguation is the use of decision list algorithm which is a supervised method. Supervised methods are considered as the most accurate machine learning algorithms but they are strongly influenced by knowledge acquisition bottleneck which means that their efficiency depends on the size of the tagged training set, in which their preparation is difficult, time-consuming and costly. The proposed method in this article improves the efficiency of this algorithm where there is a small tagged training set. This method uses a statistical method for collocation extraction from a big untagged corpus. Thus, the more important collocations which are the features used for creation of learning hypotheses will be identified. Weighting the features improves the efficiency and accuracy of a decision list algorithm which has been trained with a small training corpus.