Embryo classification beyond pregnancy: early prediction of first trimester miscarriage using machin...
Embryo classification beyond pregnancy: early prediction of first trimester miscarriage using machine learning
About this item
Full title
Author / Creator
Publisher
New York: Springer US
Journal title
Language
English
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Publication information
Publisher
New York: Springer US
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Scope and Contents
Contents
Purpose
First trimester miscarriage is a major concern in IVF-ET treatments, accounting for one out of nine clinical pregnancies and for up to one out of three recognized pregnancies. To develop a machine learning classifier for predicting the risk of cleavage-stage embryos to undergo first trimester miscarriage based on time-lapse images of pre...
Alternative Titles
Full title
Embryo classification beyond pregnancy: early prediction of first trimester miscarriage using machine learning
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9935804
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9935804
Other Identifiers
ISSN
1058-0468,1573-7330
E-ISSN
1573-7330
DOI
10.1007/s10815-022-02619-5
