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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Mining of variables from embryo morphokinetics, blastocyst's morphology and patient parameters: an approach to predict the live birth in the assisted reproduction service

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Author(s):
Cheles, Doris Spinosa [1, 2] ; Dal Molin, Eloiza Adriane [1] ; Rocha, Jose Celso [1] ; Gouveia Nogueira, Marcelo Fabio [2]
Total Authors: 4
Affiliation:
[1] Sao Paulo State Univ UNESP, Sch Languages & Sci, Dept Biol Sci, Lab Matemat Aplicada, Campus Assis, Assis, SP - Brazil
[2] Sao Paulo State Univ UNESP, Sch Sci & Languages, Dept Biol Sci, Lab Micromanipulacao Embrionaria, Campus Assis, Assis, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: JORNAL BRASILEIRO DE REPRODUCAO ASSISTIDA; v. 24, n. 4, p. 470-479, OCT-DEC 2020.
Web of Science Citations: 0
Abstract

Based on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obstacles to overcome for the purpose of improving assisted reproductive success, such as intra- and inter-observer subjectivity in embryonic selection, high occurrence of multiple pregnancies, maternal and neonatal complications. Here, we compare studies that used several variables that impact the success of assisted reproduction, such as blastocyst morphology and morphokinetic aspects of embryo development as well as characteristics of the patients submitted to assisted reproduction, in order to predict embryo quality, implantation or live birth. Thereby, we emphasize the proposal of an artificial intelligence-based platform for a more objective method to predict live birth. (AU)

FAPESP's process: 12/50533-2 - GIFT: genomic improvement of fertilization traits in Danish and Brazilian cattle
Grantee:Marcelo Fábio Gouveia Nogueira
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 17/19323-5 - Classification of human embryos using the techniques of time-lapse, digital image processing and Artificial Intelligence.
Grantee:José Celso Rocha
Support Opportunities: Regular Research Grants