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DATA MINING APPROACH IN A SELECTION OF LAPAROSCOPIC TECHNIQUES

机译:腹腔镜技术选择中的数据挖掘方法

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The objective of our study is to assess and formalize the decision process in selection of different insufflation methods in women undergoing laparoscopy. Data mining analysis was performed using retrospective data that are results of 13 years of experience at University of Louisville Hospital. Information about laparoscopic procedures on 3086 women were stored in the database. Five different laparoscopic techniques where evaluated: standard transumbilical insufflation, open laparoscopy, transuterine insufflation, subcostal insufflation and direct trocar insertion technique. Using data mining approach formalized criteria, for a selection of laparoscopic techniques, are presented in a form of decision rules.
机译:我们研究的目的是评估和正式确定腹腔镜检查妇女不同吹入方法的决策过程。数据挖掘分析采用回顾性数据进行,这些数据是路易斯维尔大学医院的13年经验。有关3086名女性的腹腔镜程序的信息存储在数据库中。五种不同的腹腔镜技术,其中评估:标准的胸腔内吹入,开放腹腔镜,过渡粉末,骨腐蚀,直接套管针插入技术。使用数据挖掘方法,以各种决策规则呈现腹腔镜技术的正式标准。

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