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The behaviour of random forest permutation-based variable importance measures under predictor correlation

BMC bioinformatics, 2010-02, Vol.11 (1), p.110-110, Article 110

2010

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The clinical phenotypes of the juvenile idiopathic inflammatory myopathies

Medicine (Baltimore), 2013-01, Vol.92 (1), p.25-41

2013

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Detecting gene-gene interactions using a permutation-based random forest method

BioData mining, 2016-04, Vol.9 (14), p.14-14, Article 14

2016

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Brief review of regression-based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience

Genetic epidemiology, 2011, Vol.35 (S1), p.S5-S11

2011

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What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics

Human genetics, 2022-09, Vol.141 (9), p.1515-1528

2022

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Automated polyp detection at CT colonography: feasibility assessment in a human population

Radiology, 2001-04, Vol.219 (1), p.51

2001

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Predictor correlation impacts machine learning algorithms: implications for genomic studies

Bioinformatics, 2009-08, Vol.25 (15), p.1884-1890

2009

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Global analysis of X-chromosome dosage compensation

Journal of biology (London, England), 2006, Vol.5 (1), p.3-3

2006

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Colonic polyps: complementary role of computer-aided detection in CT colonography

Radiology, 2002-11, Vol.225 (2), p.391

2002

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Joint Distributions and Quantum Nonlocal Models

Axioms, 2014-06, Vol.3 (2), p.166-176

2014

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Classical Probability and Quantum Outcomes

Axioms, 2014-06, Vol.3 (2), p.244-259

Malley, James D

2014

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COBRA: A combined regression strategy

Journal of multivariate analysis, 2016-04, Vol.146, p.18-28

2016

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Comparative validation of the D. melanogaster modENCODE transcriptome annotation

Genome research, 2014-07, Vol.24 (7), p.1209

2014

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Synthetic learning machines

BioData mining, 2014-12, Vol.7 (1), p.28-28, Article 28

2014

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A simplified basis for Bell–Kochen–Specker theorems

Physics letters. A, 2014-07, Vol.378 (35), p.2611-2613

2014

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Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory

Biometrical journal, 2014-07, Vol.56 (4), p.534-563

2014

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SCORHE: A novel and practical approach to video monitoring of laboratory mice housed in vivarium cage racks

Behavior research methods, 2015-03, Vol.47 (1), p.235-250

2015

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r2VIM: A new variable selection method for random forests in genome-wide association studies

BioData mining, 2016-02, Vol.9 (7), p.7-7, Article 7

2016

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New genes involved in cancer identified by retroviral tagging

Nature genetics, 2002-09, Vol.32 (1), p.166-174

2002

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Multiple neural network classification scheme for detection of colonic polyps in CT colonography data sets

Academic radiology, 2003-02, Vol.10 (2), p.154-160

2003

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Comparison of Juvenile Feed Protocols on Growth and Spawning in Zebrafish

Journal of the American Association for Laboratory Animal Science, 2021-05, Vol.60 (3), p.298-305

2021

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Using multivariate machine learning methods and structural MRI to classify childhood onset schizophrenia and healthy controls

Frontiers in psychiatry, 2012, Vol.3, p.53-53

2012

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Looking for childhood-onset schizophrenia: diagnostic algorithms for classifying children and adolescents with psychosis

Journal of child and adolescent psychopharmacology, 2014-09, Vol.24 (7), p.366

2014

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A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

Genetic epidemiology, 2014-04, Vol.38 (3), p.209-219

2014

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The behaviour of random forest permutation-based variable importance measures under predictor correlation

The clinical phenotypes of the juvenile idiopathic inflammatory myopathies

Detecting gene-gene interactions using a permutation-based random forest method

Brief review of regression-based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience

What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics

Automated polyp detection at CT colonography: feasibility assessment in a human population

Predictor correlation impacts machine learning algorithms: implications for genomic studies

Global analysis of X-chromosome dosage compensation

Colonic polyps: complementary role of computer-aided detection in CT colonography

Joint Distributions and Quantum Nonlocal Models

Classical Probability and Quantum Outcomes

COBRA: A combined regression strategy

Comparative validation of the D. melanogaster modENCODE transcriptome annotation

Synthetic learning machines

A simplified basis for Bell–Kochen–Specker theorems

Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory

SCORHE: A novel and practical approach to video monitoring of laboratory mice housed in vivarium cage racks

r2VIM: A new variable selection method for random forests in genome-wide association studies

New genes involved in cancer identified by retroviral tagging

Multiple neural network classification scheme for detection of colonic polyps in CT colonography data sets

Comparison of Juvenile Feed Protocols on Growth and Spawning in Zebrafish

Using multivariate machine learning methods and structural MRI to classify childhood onset schizophrenia and healthy controls

Looking for childhood-onset schizophrenia: diagnostic algorithms for classifying children and adolescents with psychosis

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

Immunogenetic risk and protective factors for the idiopathic inflammatory myopathies: distinct HLA-A, -B, -Cw, -DRB1, and -DQA1 allelic profiles distinguish European American patients with different myositis autoantibodies

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