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Improving machine learning performance by removing redundant cases in medical data sets

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Improving machine learning performance by removing redundant cases in medical data sets (English)

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L Ohno-Machado

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9929274

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H S Fraser

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A Ohrn

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publication date

1 January 1998

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Proceedings. AMIA Annual Symposium

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523-527

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cites work

Early diagnosis of acute myocardial infarction using clinical and electrocardiographic data at presentation: derivation and evaluation of logistic regression models

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PubMed Central

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=2232167

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21 June 2018

The meaning and use of the area under a receiver operating characteristic (ROC) curve

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https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=2232167

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21 June 2018

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2232167

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Europe PubMed Central

PubMed publication ID

9929274

retrieved

5 July 2017

PubMed publication ID

9929274

1 reference

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Europe PubMed Central

PubMed publication ID

9929274

retrieved

5 July 2017

(Q31917238)

Improving machine learning performance by removing redundant cases in medical data sets

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