Proof of concept and development of a couple-based machine learning model to stratify infertile patients with idiopathic infertility
We aimed to develop and evaluate a machine learning model that can stratify infertile/fertile couples on the basis of their bioclinical signature helping the management of couples with unexplained infertility. Fertile and infertile couples were recruited in the ALIFERT cross-sectional case–control m...
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Veröffentlicht in: | Scientific reports 2021-12, Vol.11 (1), p.24003-24003, Article 24003 |
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Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We aimed to develop and evaluate a machine learning model that can stratify infertile/fertile couples on the basis of their bioclinical signature helping the management of couples with unexplained infertility. Fertile and infertile couples were recruited in the ALIFERT cross-sectional case–control multicentric study between September 2009 and December 2013 (NCT01093378). The study group consisted of 97 infertile couples presenting a primary idiopathic infertility (> 12 months) from 4 French infertility centers compared with 100 fertile couples (with a spontaneously conceived child ( |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-021-03165-3 |