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• W2912181350 abstract "The degree of Allele sharing of the Human Leukocyte Antigen (HLA) genes has been linked with recurrent miscarriage (RM). However, no clear genetic markers of RM have yet been identified, possibly because of the complexity of interactions between paternal and maternal genes during embryo development. We propose a methodology to analyse HLA haplotypes from couples either with histories of successful pregnancies or RM. This article describes a method of RM genetic-risk calculation. The proposed HLA representation techniques allowed us to create an algorithm (IMMATCH) to retrospectively predict RM with an AUC = 0.71 (p = 0.0035) thanks to high-resolution typing and the use of linear algebra on peptide binding affinity data. The algorithm features an adjustable threshold to increase either sensitivity or specificity, allowing a sensitivity of 86%. Combining immunogenetics with artificial intelligence could create personalised tools to better understand the genetic causes of unexplained infertility and a gamete matching platform that could increase pregnancy success rates." @default.
• W2912181350 created "2019-02-21" @default.
• W2912181350 creator A5045316755 @default.
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• W2912181350 date "2019-03-07" @default.
• W2912181350 modified "2023-10-17" @default.
• W2912181350 title "Towards a gamete matching platform: using immunogenetics and artificial intelligence to predict recurrent miscarriage" @default.
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• W2912181350 doi "https://doi.org/10.1038/s41746-019-0089-x" @default.
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