Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources

Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources

To better understand information about human health from databases we analyzed three datasets collected for different purposes in Canada: a biomedical database of older adults, a large population survey across all adult ages, and vital statistics. Redundancy in the variables was established, and thi...

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Bibliographic Details
Main Authors: A Mitnitski, A Mogilner, C MacKnight, K Rockwood
Format: Article
Language:English
Published: Ubiquity Press 2003-01-01
Series:Data Science Journal
Subjects:
CODATA
Biomedical data
Mortality
Macroscopic State variable
Ageing
Frailty
Biological constants
Online Access:http://datascience.codata.org/articles/197
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spelling doaj-020f2af2173d4134958a45d3522328942020-11-24T22:57:52ZengUbiquity PressData Science Journal1683-14702003-01-012253410.2481/dsj.2.25197Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sourcesA Mitnitski0A Mogilner1C MacKnight2K Rockwood3Dept of Medicine, Dalhousie University, Halifax, NS B3H 2Y9 Dept of Computer Science, Dalhousie University, Halifax, NS B3H 2Y9Dept of Medicine, Dalhousie University, Halifax, NS B3H 2Y9Dept of Medicine, Dalhousie University, Halifax, NS B3H 2Y9Dept of Medicine, Dalhousie University, Halifax, NS B3H 2Y9To better understand information about human health from databases we analyzed three datasets collected for different purposes in Canada: a biomedical database of older adults, a large population survey across all adult ages, and vital statistics. Redundancy in the variables was established, and this led us to derive a generalized (macroscopic state) variable, being a fitness/frailty index that reflects both individual and group health status. Evaluation of the relationship between fitness/frailty and the mortality rate revealed that the latter could be expressed in terms of variables generally available from any cross-sectional database. In practical terms, this means that the risk of mortality might readily be assessed from standard biomedical appraisals collected for other purposes.http://datascience.codata.org/articles/197CODATABiomedical dataMortalityMacroscopic State variableAgeingFrailtyBiological constants
collection DOAJ
language English
format Article
sources DOAJ
author A Mitnitski
A Mogilner
C MacKnight
K Rockwood
spellingShingle A Mitnitski
A Mogilner
C MacKnight
K Rockwood
Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources
Data Science Journal
CODATA
Biomedical data
Mortality
Macroscopic State variable
Ageing
Frailty
Biological constants
author_facet A Mitnitski
A Mogilner
C MacKnight
K Rockwood
author_sort A Mitnitski
title Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources
title_short Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources
title_full Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources
title_fullStr Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources
title_full_unstemmed Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources
title_sort data integration and knowledge discovery in biomedical databases. reliable information from unreliable sources
publisher Ubiquity Press
series Data Science Journal
issn 1683-1470
publishDate 2003-01-01
description To better understand information about human health from databases we analyzed three datasets collected for different purposes in Canada: a biomedical database of older adults, a large population survey across all adult ages, and vital statistics. Redundancy in the variables was established, and this led us to derive a generalized (macroscopic state) variable, being a fitness/frailty index that reflects both individual and group health status. Evaluation of the relationship between fitness/frailty and the mortality rate revealed that the latter could be expressed in terms of variables generally available from any cross-sectional database. In practical terms, this means that the risk of mortality might readily be assessed from standard biomedical appraisals collected for other purposes.
topic CODATA
Biomedical data
Mortality
Macroscopic State variable
Ageing
Frailty
Biological constants
url http://datascience.codata.org/articles/197
work_keys_str_mv AT amitnitski dataintegrationandknowledgediscoveryinbiomedicaldatabasesreliableinformationfromunreliablesources
AT amogilner dataintegrationandknowledgediscoveryinbiomedicaldatabasesreliableinformationfromunreliablesources
AT cmacknight dataintegrationandknowledgediscoveryinbiomedicaldatabasesreliableinformationfromunreliablesources
AT krockwood dataintegrationandknowledgediscoveryinbiomedicaldatabasesreliableinformationfromunreliablesources
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