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From data collection to knowledge data discovery: a medical application of data mining.

机译:从数据收集到知识数据发现:数据挖掘的医学应用。

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Prison inmates are exposed to a variety of major risk factors (psychiatric disorders, suicide attempts, illicit drug use). From 1986 to 1996, the USA prison population more than doubled while in France, it increased from 35655 in 1980 to 51623 in 1995. In spite of these findings, very little information concerning the inmates population is available. At the present time, there is a desire to adopt a policy based on the prevention of recidivism, on adequate release planning and referrals to community-based services. The aim of the RAPPEL project was to build an information system for assessing the social and health status of prison inmates. The pilot project was set up at the prison of Loos and allowed the collection and analysis of nearly 15000 records. The aim of this paper is to present the extension of the project consisting in developing a regional network grouping 11 jails. Information locally available will serve as the basis for the information system of regional jails. Data mining techniques will provide solutions for the extraction of new information. Three data mining tools were experimented : association rules, classification trees and clustering. Further extension consists in a distributed approach allowing direct access to the information system by WEB tools.
机译:监狱囚犯暴露于各种主要危险因素(精神病疾病,自杀企图,非法药物使用)。从1986年到1996年,美国监狱人口在法国增加了一倍多,它从1980年的35655增加到1995年的51623。尽管有这些调查结果,可以获得有关囚犯人口的少数人。目前,愿望采取基于预防累犯的政策,就足够的释放规划和基于社区服务的推荐。 rappel项目的目的是建立一个评估监狱囚犯社会和健康状况的信息系统。试点项目在LOOS监狱设立,允许收集和分析近15000条记录。本文的目的是展示在制定区域网络分组11监狱的项目的延伸。当地可用的信息将作为区域监狱信息系统的基础。数据挖掘技术将为提取新信息提供解决方案。实验三个数据挖掘工具:关联规则,分类树和聚类。进一步的扩展包括分布式方法,允许通过Web工具直接访问信息系统。

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