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Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data

dc.contributor.authorFernandez, Eleonora Inácio [UNESP]
dc.contributor.authorFerreira, André Satoshi [UNESP]
dc.contributor.authorCecílio, Matheus Henrique Miquelão [UNESP]
dc.contributor.authorChéles, Dóris Spinosa [UNESP]
dc.contributor.authorde Souza, Rebeca Colauto Milanezi [UNESP]
dc.contributor.authorNogueira, Marcelo Fábio Gouveia [UNESP]
dc.contributor.authorRocha, José Celso [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-12T02:14:56Z
dc.date.available2020-12-12T02:14:56Z
dc.date.issued2020-01-01
dc.description.abstractOver the past years, the assisted reproductive technologies (ARTs) have been accompanied by constant innovations. For instance, intracytoplasmic sperm injection (ICSI), time-lapse monitoring of the embryonic morphokinetics, and PGS are innovative techniques that increased the success of the ART. In the same trend, the use of artificial intelligence (AI) techniques is being intensively researched whether in the embryo or spermatozoa selection. Despite several studies already published, the use of AI within assisted reproduction clinics is not yet a reality. This is largely due to the different AI techniques that are being proposed to be used in the daily routine of the clinics, which causes some uncertainty in their use. To shed light on this complex scenario, this review briefly describes some of the most frequently used AI algorithms, their functionalities, and their potential use. Several databases were analyzed in search of articles where applied artificial intelligence algorithms were used on reproductive data. Our focus was on the classification of embryonic cells and semen samples. Of a total of 124 articles analyzed, 32 were selected for this review. From the proposed algorithms, most have achieved a satisfactory precision, demonstrating the potential of a wide range of AI techniques. However, the evaluation of these studies suggests the need for more standardized research to validate the proposed models and their algorithms. Routine use of AI in assisted reproduction clinics is just a matter of time. However, the choice of AI technique to be used is supported by a better understanding of the principles subjacent to each technique, that is, its robustness, pros, and cons. We provide some current (although incipient) and potential uses of AI on the clinic routine, discussing how accurate and friendly it could be. Finally, we propose some standards for AI research on the selection of the embryo to be transferred and other future hints. For us, the imminence of its use is evident, providing a revolutionary milestone that will impact the ART.en
dc.description.affiliationLaboratory of Applied Mathematics Department of Biological Sciences São Paulo State University (UNESP), Campus Assis, Av. Dom Antônio
dc.description.affiliationLaboratory of Embryonic Micromanipulation Department of Biological Sciences São Paulo State University (UNESP), Campus Assis, Av. Dom Antônio
dc.description.affiliationUniversidade Estadual Paulista Julio de Mesquita Filho, Assis
dc.description.affiliationUnespLaboratory of Applied Mathematics Department of Biological Sciences São Paulo State University (UNESP), Campus Assis, Av. Dom Antônio
dc.description.affiliationUnespLaboratory of Embryonic Micromanipulation Department of Biological Sciences São Paulo State University (UNESP), Campus Assis, Av. Dom Antônio
dc.description.affiliationUnespUniversidade Estadual Paulista Julio de Mesquita Filho, Assis
dc.identifierhttp://dx.doi.org/10.1007/s10815-020-01881-9
dc.identifier.citationJournal of Assisted Reproduction and Genetics.
dc.identifier.doi10.1007/s10815-020-01881-9
dc.identifier.issn1573-7330
dc.identifier.issn1058-0468
dc.identifier.scopus2-s2.0-85087820350
dc.identifier.urihttp://hdl.handle.net/11449/200747
dc.language.isoeng
dc.relation.ispartofJournal of Assisted Reproduction and Genetics
dc.sourceScopus
dc.subjectArtificial intelligence
dc.subjectAssisted reproductive technologies
dc.subjectDeep learning
dc.subjectEmbryo classification
dc.subjectMultilayer perceptron
dc.subjectPrediction models
dc.titleArtificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive dataen
dc.typeResenha
dspace.entity.typePublication
unesp.author.orcid0000-0002-2239-9652[6]
unesp.author.orcid0000-0002-0094-2634[7]
unesp.departmentCiências Biológicas - FCLASpt

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