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A combination of immune cell types identified through ensemble machine learning strategy detects altered profile in recurrent pregnancy loss: a pilot study.

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Title: A combination of immune cell types identified through ensemble machine learning strategy detects altered profile in recurrent pregnancy loss: a pilot study.
Authors: Benner M; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands., Feyaerts D; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands., Lopez-Rincon A; Department of Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands., van der Heijden OWH; Department of Obstetrics and Gynecology, Radboud University Medical Center, Nijmegen, the Netherlands., van der Hoorn ML; Department of Gynecology and Obstetrics, Leiden University Medical Center, Leiden, the Netherlands., Joosten I; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands., Ferwerda G; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands., van der Molen RG; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands. Electronic address: Renate.vanderMolen@radboudumc.nl.
Source: F&S science [F S Sci] 2022 May; Vol. 3 (2), pp. 166-173. Date of Electronic Publication: 2022 Feb 09.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Elsevier Inc Country of Publication: United States NLM ID: 101765857 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2666-335X (Electronic) Linking ISSN: 2666335X NLM ISO Abbreviation: F S Sci Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Benner+M%22">Benner M</searchLink>; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Feyaerts+D%22">Feyaerts D</searchLink>; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Lopez-Rincon+A%22">Lopez-Rincon A</searchLink>; Department of Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands.<br /><searchLink fieldCode="AU" term="%22van+der+Heijden+OWH%22">van der Heijden OWH</searchLink>; Department of Obstetrics and Gynecology, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22van+der+Hoorn+ML%22">van der Hoorn ML</searchLink>; Department of Gynecology and Obstetrics, Leiden University Medical Center, Leiden, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Joosten+I%22">Joosten I</searchLink>; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22Ferwerda+G%22">Ferwerda G</searchLink>; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands.<br /><searchLink fieldCode="AU" term="%22van+der+Molen+RG%22">van der Molen RG</searchLink>; Radboud Institute of Molecular Life Sciences, Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Center, Nijmegen, the Netherlands. Electronic address: Renate.vanderMolen@radboudumc.nl.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Inc%22">Elsevier Inc </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101765857 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2666-335X (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%222666335X%22">2666335X </searchLink><i>NLM ISO Abbreviation: </i>F S Sci <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.xfss.2022.02.002
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        Text: English
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              Text: 2022 May
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