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Journal of Assisted Reproduction and Genetics

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01-08-2017 | Embryo Biology

Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics

Authors: Beatriz Carrasco, Gemma Arroyo, Yolanda Gil, Mª José Gómez, Ignacio Rodríguez, Pedro N. Barri, Anna Veiga, Montserrat Boada

Published in: Journal of Assisted Reproduction and Genetics | Issue 8/2017

Abstract

Purpose

The objective of this work was to determine which embryonic morphokinetic parameters up to D3 of in vitro development have predictive value for implantation for the selection of embryos for transfer in clinical practice based upon information generated from embryo transfers with known implantation data (KID).

Methods

A total of 800 KID embryos (100% implantation rate (IR) per transfer and 0% IR per transfer) cultured in an incubator with Time-Lapse system were retrospectively analysed. Of them, 140 embryos implanted, whereas 660 did not.

Results

The analysis of morphokinetic parameters, together with the embryo morphology assessment on D3, enabled us to develop a hierarchical model that places the classical morphological score, the t4 and t8 morphokinetic values, as the variables with the best prognosis of implantation.

Conclusion

In our decision tree, the classical morphological score is the most predictive parameter. Among embryos with better morphological scores, morphokinetics permits deselection of embryos with the lowest implantation potential.

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Title: Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics
Authors: Beatriz Carrasco
Gemma Arroyo
Yolanda Gil
Mª José Gómez
Ignacio Rodríguez
Pedro N. Barri
Anna Veiga
Montserrat Boada
Publication date: 01-08-2017
Publisher: Springer US
Published in: Journal of Assisted Reproduction and Genetics / Issue 8/2017
Print ISSN: 1058-0468
Electronic ISSN: 1573-7330
DOI: https://doi.org/10.1007/s10815-017-0955-x

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Selecting embryos with the highest implantation potential using data mining and decision tree based on classical embryo morphology and morphokinetics

Abstract

Purpose

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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