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Logistic regression and artificial neural network classification models: a methodology review
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scholarly article
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stated in
Q5412157
PubMed ID
12968784
retrieved
7 August 2017
review article
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Q5412157
title
Logistic regression and artificial neural network classification models: a methodology review
(English)
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Q5412157
PubMed ID
12968784
retrieved
7 August 2017
main subject
logistic regression model
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inferred from title
artificial neural network
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author
Lucila Ohno-Machado
series ordinal
2
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Q5412157
PubMed ID
12968784
retrieved
7 August 2017
reference URL
https://orcid.org/0000-0002-8005-7327
author name string
Stephan Dreiseitl
series ordinal
1
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Q5412157
PubMed ID
12968784
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7 August 2017
publication date
1 October 2002
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Q5412157
PubMed ID
12968784
retrieved
7 August 2017
published in
Journal of Biomedical Informatics
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Q5412157
PubMed ID
12968784
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7 August 2017
volume
35
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Q5412157
PubMed ID
12968784
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7 August 2017
page(s)
352-359
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Q5412157
PubMed ID
12968784
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7 August 2017
issue
5-6
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Q5412157
PubMed ID
12968784
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7 August 2017
cites work
A method of comparing the areas under receiver operating characteristic curves derived from the same cases
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Crossref
reference URL
https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach
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https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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What do we mean by validating a prognostic model?
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reference URL
https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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Validity of prognostic models: when is a model clinically useful?
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https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology.
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https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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A review of evidence of health benefit from artificial neural networks in medical intervention
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https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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A comparison of machine learning methods for the diagnosis of pigmented skin lesions.
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7 January 2021
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Support vector machines for diagnosis of breast tumors on US images
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On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach
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Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
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https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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Neural networks and the roles of cross validation.
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reference URL
https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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Neural networks, logistic regression, and calibration
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reference URL
https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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Neural Networks, Logistic Regression, and Calibration: A Rejoinder
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reference URL
https://api.crossref.org/works/10.1016%2FS1532-0464%2803%2900034-0
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7 January 2021
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Identifiers
DOI
10.1016/S1532-0464(03)00034-0
1 reference
stated in
Q5412157
PubMed ID
12968784
retrieved
7 August 2017
DBLP publication ID
journals/jbi/DreiseitlO02
1 reference
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DBLP Dataset 2021-01-02
retrieved
28 January 2021
PubMed ID
12968784
1 reference
stated in
Q5412157
PubMed ID
12968784
retrieved
7 August 2017
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