Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology

José Celso Rocha, Diogo Lima Bezerra da Silva, João Guilherme Cândido dos Santos, Lucy Benham Whyte, Cristina Hickman, Stuart Lavery, Marcelo Fábio Gouveia Nogueira

2017

Abstract

The morphology of the human embryo produced by in vitro fertilized (IVF) is historically used as a predictive marker of gestational success. Although there are several different proposed methods to improve determination of embryo morphology, currently, all methods rely on a manual, optical and subjective evaluation done by an embryologist. Given that tiredness, mood and distinct experience could influence the accuracy of the evaluation, the results found are very different from embryologist to embryologist and from clinic to clinic. We propose the use of an objective evaluation, with repeatability and automatization, of the human blastocyst by image processing and the use of Artificial Neural Network (i.e., Artificial Intelligence).

Paper Citation

in Harvard Style

Rocha J., Bezerra da Silva D., dos Santos J., Whyte L., Hickman C., Lavery S. and Gouveia Nogueira M. (2017). Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology.In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-274-5, pages 354-359. DOI: 10.5220/0006515803540359

in Bibtex Style

@conference{ijcci17,
author={José Celso Rocha and Diogo Lima Bezerra da Silva and João Guilherme Cândido dos Santos and Lucy Benham Whyte and Cristina Hickman and Stuart Lavery and Marcelo Fábio Gouveia Nogueira},
title={Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology},
booktitle={Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2017},
pages={354-359},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006515803540359},
isbn={978-989-758-274-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology
SN - 978-989-758-274-5
AU - Rocha J.
AU - Bezerra da Silva D.
AU - dos Santos J.
AU - Whyte L.
AU - Hickman C.
AU - Lavery S.
AU - Gouveia Nogueira M.
PY - 2017
SP - 354
EP - 359
DO - 10.5220/0006515803540359