The use of voting ensembles to improve the accuracy of deep neural networks as a non-invasive method...
The use of voting ensembles to improve the accuracy of deep neural networks as a non-invasive method to predict embryo ploidy status
About this item
Full title
Author / Creator
Publisher
New York: Springer US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Springer US
Subjects
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Scope and Contents
Contents
Purpose
To determine if creating voting ensembles combining convolutional neural networks (CNN), support vector machine (SVM), and multi-layer neural networks (NN) alongside clinical parameters improves the accuracy of artificial intelligence (AI) as a non-invasive method for predicting aneuploidy.
Methods
A cohort of 699 day 5 PGT-A teste...
Alternative Titles
Full title
The use of voting ensembles to improve the accuracy of deep neural networks as a non-invasive method to predict embryo ploidy status
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9935776
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9935776
Other Identifiers
ISSN
1058-0468
E-ISSN
1573-7330
DOI
10.1007/s10815-022-02707-6
