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Data-mining technologies for diabetes: a systematic review

Data-mining technologies for diabetes: a systematic review

http://www.wikidata.org/entity/Q26863015

about

A machine learning-based framework to identify type 2 diabetes through electronic health records.Detecting intentional insulin omission for weight loss in girls with type 1 diabetes mellitus.

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Data-mining technologies for diabetes: a systematic review

http://www.wikidata.org/entity/Q26863015

description

2011 nî lūn-bûn

@nan

2011 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

@hyw

2011 թվականի նոյեմբերին հրատարակված գիտական հոդված

@hy

2011年の論文

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2011年論文

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2011年論文

@zh-hant

2011年論文

@zh-hk

2011年論文

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2011年論文

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2011年论文

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name

Data-mining technologies for diabetes: a systematic review

@ast

Data-mining technologies for diabetes: a systematic review

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Data-mining technologies for diabetes: a systematic review

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type

label

Data-mining technologies for diabetes: a systematic review

@ast

Data-mining technologies for diabetes: a systematic review

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Data-mining technologies for diabetes: a systematic review

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prefLabel

Data-mining technologies for diabetes: a systematic review

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Data-mining technologies for diabetes: a systematic review

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Data-mining technologies for diabetes: a systematic review

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193229681100500631

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Journal of Diabetes Science and Technology

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Data-mining technologies for diabetes: a systematic review

@en

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Illhoi Yoo

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Miroslav Marinov

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P2860

Searching QTL by gene expression: analysis of diabesity

Data mining for indicators of early mortality in a database of clinical records.

Novel statistical classification model of type 2 diabetes mellitus patients for tailor-made prevention using data mining algorithm.

Data mining a diabetic data warehouse.

A preprocessing method for improving data mining techniques. Application to a large medical diabetes database.

New data analysis and mining approaches identify unique proteome and transcriptome markers of susceptibility to autoimmune diabetes.

Application of information-theoretic data mining techniques in a national ambulatory practice outcomes research network.

ExQuest, a novel method for displaying quantitative gene expression from ESTs.

Prediction of blood glucose level of type 1 diabetics using response surface methodology and data mining.

Outcomes of educational interventions in type 2 diabetes: WEKA data-mining analysis.

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1549-1556

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scholarly article

systematic review

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10.1177/193229681100500631

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6

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5

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Abu Saleh Mohammad Mosa

Suzanne A Boren

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2011-11-01T00:00:00Z

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22226277

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