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Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology

Topics: Applications: Image Processing and Artificial Vision, Pattern Recognition, Decision Making, Industrial and Real World applications, Financial Applications, Neural Prostheses and Medical Applications, Neural based Data Mining and Complex Information Processing, Neural Network Software and Applications, Applications of Deep Neural networks, Robotics and Control Applications

Authors: José Celso Rocha 1 ; Diogo Lima Bezerra da Silva 1 ; João Guilherme Cândido dos Santos 1 ; Lucy Benham Whyte 2 ; Cristina Hickman 3 ; Stuart Lavery 3 and Marcelo Fábio Gouveia Nogueira 4

Affiliations: 1 Laboratório de Matemática Aplicada, FCL and Universidade Estadual Paulista (Unesp), Brazil ; 2 Boston Place Clinic and University of Oxford, United Kingdom ; 3 Boston Place Clinic and Imperial College London, United Kingdom ; 4 Laboratório de Micromanipulação Embrionária, FCL and Unesp, Brazil

Keyword(s): Artificial Intelligence, Human Embryo, Embryo Classification, Image Digital Processing.

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).

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Paper citation in several formats:
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 (IJCCI 2017) - IJCCI; ISBN 978-989-758-274-5; ISSN 2184-3236, SciTePress, pages 354-359. DOI: 10.5220/0006515803540359

@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 (IJCCI 2017) - IJCCI},
year={2017},
pages={354-359},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006515803540359},
isbn={978-989-758-274-5},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Computational Intelligence (IJCCI 2017) - IJCCI
TI - Using Artificial Intelligence to Improve the Evaluation of Human Blastocyst Morphology
SN - 978-989-758-274-5
IS - 2184-3236
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
PB - SciTePress

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