医学中的数据挖掘问题

Ciril Groselj
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引用次数: 8

摘要

任何基于患者数据的回顾性调查的原则是按问题或体征搜索患者,而不是按姓名。使用适当的问题编码档案数据库,数据挖掘过程将很容易。人们只需要在短时间内输入请求并获得适当的数据。医疗档案通常仅以纸质记录为基础,以患者姓名作为输入键。为了在这样的存档中找到正确的记录,需要一种检测策略。这个过程继续收集通常数量巨大的文件,在其中找到适当的记录,最后对它们进行编码并排列在表格中。整个过程可分为病人、论文和数据挖掘。由于进展缓慢,这些阶段可能是基于医学数据的调查中最耗时的部分。作者描述了他的数据挖掘经验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data mining problems in medicine
The principle of any retrospective on patient data-based investigation is searching the patients by problem or sign, but not by name. With a proper problem-encoded archival database, the data mining process would be easy. One would only need to input the request and obtain the proper data in a short time. Medical archives are frequently based on paper records only, with the patient name as the entry key. To find the proper record in such an archive, a detection strategy is needed. The process continues with collecting the usually enormous amount of papers, finding the appropriate records within them, and finally encoding and arranging them in a table. The whole process can be separated into patients, paper and data mining. Because of their slowness, these phases can be the most time-consuming part of a medical data-based investigation. The author describes his data mining experience.
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