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1
A systematic comparison of supervised classifiers
A systematic comparison of supervised classifiers
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A systematic comparison of supervised classifiers

PloS one, 2014-04, Vol.9 (4), p.e94137-e94137 [Peer Reviewed Journal]

COPYRIGHT 2014 Public Library of Science ;COPYRIGHT 2014 Public Library of Science ;2014 Amancio et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2014 Amancio et al 2014 Amancio et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0094137 ;PMID: 24763312

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2
Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection
Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection
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Ultra-high-throughput clinical proteomics reveals classifiers of COVID-19 infection

Cell Systems, 2020-07, Vol.11 (1), p.11 [Peer Reviewed Journal]

2020. Not withstanding the ProQuest Terms and Conditions, you may use this content in accordance with the associated terms available at https://www.elsevier.com/legal/elsevier-website-terms-and-conditions ;ISSN: 2405-4720 ;ISSN: 2405-4712 ;EISSN: 2405-4720 ;DOI: 10.1016/j.cels.2020.05.012

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3
A performance comparison of eight commercially available automatic classifiers for facial affect recognition
A performance comparison of eight commercially available automatic classifiers for facial affect recognition
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A performance comparison of eight commercially available automatic classifiers for facial affect recognition

PloS one, 2020-04, Vol.15 (4), p.e0231968-e0231968 [Peer Reviewed Journal]

COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Dupré et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Dupré et al 2020 Dupré et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0231968 ;PMID: 32330178

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4
Comprehensive benchmarking and ensemble approaches for metagenomic classifiers
Comprehensive benchmarking and ensemble approaches for metagenomic classifiers
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Comprehensive benchmarking and ensemble approaches for metagenomic classifiers

Genome Biology, 2017-09, Vol.18 (1), p.182-19, Article 182 [Peer Reviewed Journal]

2017. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s). 2017 ;ISSN: 1474-760X ;ISSN: 1474-7596 ;EISSN: 1474-760X ;DOI: 10.1186/s13059-017-1299-7 ;PMID: 28934964

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5
Differentiation of supratentorial single brain metastasis and glioblastoma by using peri-enhancing oedema region–derived radiomic features and multiple classifiers
Differentiation of supratentorial single brain metastasis and glioblastoma by using peri-enhancing oedema region–derived radiomic features and multiple classifiers
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Differentiation of supratentorial single brain metastasis and glioblastoma by using peri-enhancing oedema region–derived radiomic features and multiple classifiers

European radiology, 2020-05, Vol.30 (5), p.3015-3022 [Peer Reviewed Journal]

European Society of Radiology 2019 ;European Society of Radiology 2019. ;ISSN: 0938-7994 ;EISSN: 1432-1084 ;DOI: 10.1007/s00330-019-06460-w ;PMID: 32006166

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6
Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers
Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers
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Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers

NeuroImage (Orlando, Fla.), 2014-04, Vol.90, p.449-468 [Peer Reviewed Journal]

2014 ;2015 INIST-CNRS ;Copyright © 2014. Published by Elsevier Inc. ;Copyright Elsevier Limited Apr 15, 2014 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2013.11.046 ;PMID: 24389422

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7
Class-imbalanced classifiers for high-dimensional data
Class-imbalanced classifiers for high-dimensional data
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Class-imbalanced classifiers for high-dimensional data

Briefings in bioinformatics, 2013-01, Vol.14 (1), p.13-26 [Peer Reviewed Journal]

ISSN: 1467-5463 ;EISSN: 1477-4054 ;DOI: 10.1093/bib/bbs006 ;PMID: 22408190

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8
The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets
The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets
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The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets

PloS one, 2015-03, Vol.10 (3), p.e0118432-e0118432 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Saito, Rehmsmeier. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Saito, Rehmsmeier 2015 Saito, Rehmsmeier ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0118432 ;PMID: 25738806

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9
Machine learning classifiers and fMRI: A tutorial overview
Machine learning classifiers and fMRI: A tutorial overview
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Machine learning classifiers and fMRI: A tutorial overview

NeuroImage (Orlando, Fla.), 2009-03, Vol.45 (1), p.S199-S209 [Peer Reviewed Journal]

2008 Elsevier Inc. ;Copyright Elsevier Limited Mar 1, 2009 ;ISSN: 1053-8119 ;EISSN: 1095-9572 ;DOI: 10.1016/j.neuroimage.2008.11.007 ;PMID: 19070668

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10
MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers
MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers
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MRI-Based Brain Tumor Classification Using Ensemble of Deep Features and Machine Learning Classifiers

Sensors (Basel, Switzerland), 2021-03, Vol.21 (6), p.2222 [Peer Reviewed Journal]

2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21062222 ;PMID: 33810176

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11
Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers
Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers
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Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers

Medical physics (Lancaster), 2018-07, Vol.45 (7), p.3449-3459 [Peer Reviewed Journal]

2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine. ;ISSN: 0094-2405 ;EISSN: 2473-4209 ;DOI: 10.1002/mp.12967 ;PMID: 29763967

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12
Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data
Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data
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Feature-based classifiers for somatic mutation detection in tumour-normal paired sequencing data

Bioinformatics, 2012-01, Vol.28 (2), p.167-175 [Peer Reviewed Journal]

The Author(s) 2011. Published by Oxford University Press. 2011 ;2015 INIST-CNRS ;ISSN: 1367-4803 ;EISSN: 1460-2059 ;EISSN: 1367-4811 ;DOI: 10.1093/bioinformatics/btr629 ;PMID: 22084253

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13
Facial recognition from DNA using face-to-DNA classifiers
Facial recognition from DNA using face-to-DNA classifiers
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Facial recognition from DNA using face-to-DNA classifiers

Nature communications, 2019-06, Vol.10 (1), p.2557-2557, Article 2557 [Peer Reviewed Journal]

The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2019 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-019-10617-y ;PMID: 31186421

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14
Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study
Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study
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Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study

PloS one, 2015-12, Vol.10 (12), p.e0145118-e0145118 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Maier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Maier et al 2015 Maier et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0145118 ;PMID: 26672989

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15
Ovarian Cancer-Specific BRCA -like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial
Ovarian Cancer-Specific BRCA -like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial
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Ovarian Cancer-Specific BRCA -like Copy-Number Aberration Classifiers Detect Mutations Associated with Homologous Recombination Deficiency in the AGO-TR1 Trial

Clinical cancer research, 2021-12, Vol.27 (23), p.6559-6569 [Peer Reviewed Journal]

2021 The Authors; Published by the American Association for Cancer Research. ;2021 The Authors; Published by the American Association for Cancer Research 2021 American Association for Cancer Research ;ISSN: 1078-0432 ;EISSN: 1557-3265 ;DOI: 10.1158/1078-0432.CCR-21-1673 ;PMID: 34593530

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16
Fully automated stroke tissue estimation using random forest classifiers (FASTER)
Fully automated stroke tissue estimation using random forest classifiers (FASTER)
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Fully automated stroke tissue estimation using random forest classifiers (FASTER)

Journal of cerebral blood flow and metabolism, 2017-08, Vol.37 (8), p.2728-2741 [Peer Reviewed Journal]

The Author(s) 2016 ;The Author(s) 2016 2016 International Society for Cerebral Blood Flow and Metabolism ;ISSN: 0271-678X ;EISSN: 1559-7016 ;DOI: 10.1177/0271678X16674221 ;PMID: 27798267

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17
Contemporary QSAR Classifiers Compared
Contemporary QSAR Classifiers Compared
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Contemporary QSAR Classifiers Compared

Journal of chemical information and modeling, 2007-01, Vol.47 (1), p.219-227 [Peer Reviewed Journal]

Copyright © 2007 American Chemical Society ;ISSN: 1549-9596 ;EISSN: 1549-960X ;DOI: 10.1021/ci600332j ;PMID: 17238267

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18
Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images
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Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images

American journal of ophthalmology, 2019-12, Vol.208, p.273-280 [Peer Reviewed Journal]

2019 Elsevier Inc. ;Copyright © 2019 Elsevier Inc. All rights reserved. ;2019. Elsevier Inc. ;ISSN: 0002-9394 ;EISSN: 1879-1891 ;DOI: 10.1016/j.ajo.2019.08.004 ;PMID: 31445003

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19
Interpretable genotype-to-phenotype classifiers with performance guarantees
Interpretable genotype-to-phenotype classifiers with performance guarantees
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Interpretable genotype-to-phenotype classifiers with performance guarantees

Scientific reports, 2019-03, Vol.9 (1), p.4071-4071, Article 4071 [Peer Reviewed Journal]

This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2019 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-019-40561-2 ;PMID: 30858411

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20
Variational quantum classifiers through the lens of the Hessian
Variational quantum classifiers through the lens of the Hessian
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Variational quantum classifiers through the lens of the Hessian

PloS one, 2022-01, Vol.17 (1), p.e0262346-e0262346 [Peer Reviewed Journal]

COPYRIGHT 2022 Public Library of Science ;2022 Sen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 Sen et al 2022 Sen et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0262346 ;PMID: 35051206

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