Techniques for knowledge discovery in existing biomedical databases: Estimation of individual aging effects in cognition in relation to dementia

被引：7

作者：

Mitnitski, AB ^{[1
]}

Mogilner, AJ ^{[1
]}

Graham, JE ^{[1
]}

Rockwood, K ^{[1
]}

机构：

[1] Dalhousie Univ, Geriatr Med Res Unit, Halifax, NS B3H 2E1, Canada

来源：

JOURNAL OF CLINICAL EPIDEMIOLOGY | 2003年 / 56卷 / 02期

关键词：

dementia; knowledge discovery in databases; Bayesian statistics;

D O I：

10.1016/S0895-4356(02)00581-4

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

New interest is being expressed in the systematic application of modeling techniques to existing datasets. Under the rubric of Knowledge Discovery in Databases (KDD) large databases are being exploited for commercial and scientific purposes. This article reviews the development and applications of KDD techniques to dementia, using the longitudinal Canadian Study of Health and Aging dataset. KDD has demonstrated usefulness at the group level. For example, as in the course of functional impairment between Alzheimer's disease and no cognitive impairment suggest damage, control-protection mechanisms for the former compared with noncompensated random accumulation of deficits for the latter. At the individual level, KDD suggests that more precise diagnosis seems possible as well as individual life expectancy prediction. Biomedical databases appear to hold the potential for novel insights when explored by systematic modeling. (C) 2003 Elsevier Science Inc. All rights reserved.

引用

页码：116 / 123

页数：8

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