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dc.contributor.authorRiegler, Michael Alexander
dc.contributor.authorStensen, Mette Haug
dc.contributor.authorWitczak, Oliwia
dc.contributor.authorAndersen, Jorunn Marie
dc.contributor.authorHicks, Steven
dc.contributor.authorHammer, Hugo Lewi
dc.contributor.authorDelbarre, Erwan
dc.contributor.authorHalvorsen, Pål
dc.contributor.authorYazidi, Anis
dc.contributor.authorHolst, Nicolai
dc.contributor.authorHaugen, Trine B.
dc.date.accessioned2022-03-24T15:39:10Z
dc.date.available2022-03-24T15:39:10Z
dc.date.created2021-11-08T09:47:44Z
dc.date.issued2021-07-29
dc.identifier.issn0268-1161
dc.identifier.issn1460-2350
dc.identifier.urihttps://hdl.handle.net/11250/2987476
dc.description.abstractIn recent years, the amount of data produced in the field of assisted reproduction technology [ART] has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence [AI] is progressively taking place in medical practice and may become a promising tool to improve the success rate with ART. AI models may compensate for the lack of objectivity in several critical procedures in fertility clinics, especially embryo and sperm assessments. Various models have been developed, and even though several of them show promising performance, there are still many challenges to overcome. In this review, we present recent research on AI in the context of ART. We discuss the strengths and weaknesses of the presented methods, especially regarding clinical relevance. We also address the pitfalls hampering successful use of AI in the clinic and discuss future possibilities and important aspects to make AI truly useful for ART.en_US
dc.description.sponsorshipThe work on this article was partially funded by the Frimedbio project ReproAI granted by the Norwegian Research Council with project number 288727en_US
dc.language.isoengen_US
dc.publisherOxford University Pressen_US
dc.relation.ispartofseriesHuman Reproduction;Volume 36, Issue 9
dc.subjectArtificial intelligenceen_US
dc.subjectMachine learningen_US
dc.subjectAssisted reproductive technologyen_US
dc.subjectEmbryologyen_US
dc.subjectSemen analysesen_US
dc.subjectFertilityen_US
dc.titleArtificial intelligence in the fertility clinic: status, pitfalls and possibilitiesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.doihttps://doi.org/10.1093/humrep/deab168
dc.identifier.cristin1952194
dc.source.journalHuman Reproductionen_US
dc.source.volume36en_US
dc.source.issue9en_US
dc.source.pagenumber24en_US
dc.relation.projectNorges forskningsråd: 288727en_US


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