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An Inductive Method for Automatic Generation of Referring Physician Prefetch Rules for PACS

机译:一种自动生成PACS推荐医师预取规则的归纳方法

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摘要

To prefetch images in a hospital-wide picture archiving and communication system (PACS), a rule must be devised to permit accurate selection of examinations in which a patient's images are stored. We developed an inductive method to compose prefetch rules from practical data which were obtained in a hospital using a decision tree algorithm. Our methods were evaluated on data acquired in Osaka University Hospital for one month. The data collected consisted of 58,617 cases of consultation reservations, 643,797 examination histories of patients, and 323,993 records of image requests in PACS. Four parameters indicating whether the images of the patient were requested or not for each consultation reservation were derived from the database. As a result, the successful selection sensitivity for consultations in which images were requested was approximately 0.8, and the specificity for excluding consultations accurately where images were not requested was approximately 0.7.
机译:为了在医院范围内的图片存档和通信系统(PACS)中预取图像,必须设计规则以允许准确选择存储患者图像的检查内容。我们开发了一种归纳方法来根据实际数据构成预取规则,这些数据是在医院中使用决策树算法获得的。我们对在大阪大学医院获得的数据进行了为期一个月的评估。收集的数据包括58,617例咨询预约,643,797例患者检查历史以及323,993例PACS中的图像请求记录。从数据库中导出了四个参数,这些参数指示是否为每个咨询预约请求患者图像。结果,对于请求图像的咨询的成功选择敏感度约为0.8,并且对于在不请求图像的情况下准确地排除咨询的特异性约为0.7。

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