About: An interpretable and versatile machine learning approach for oocyte phenotyping

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About: An interpretable and versatile machine learning approach for oocyte phenotyping Goto Sponge NotDistinct Permalink

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Author	Terret, Marie-Emilie (19..-.... ; biologiste) Wolf, Jean-Philippe (19..-.... ; biologiste) Minc, Nicolas (1979-....) Verlhac, Marie-Hélène (19..-....) Crozet, Flora (1993-....)
Bibliographic Citation	Letort Gaelle, Eichmuller Adrien, da Silva Christelle, Nikalayevich Elvira, Crozet Flora, Salle Jeremy, Minc Nicolas, Labrune Elsa, Wolf Jean-Philippe, Terret Marie-Emilie, Verlhac Marie-Hélène. An interpretable and versatile machine learning approach for oocyte phenotyping. Journal of Cell Science, 2022, ⟨10.1242/jcs.260281⟩
Title	An interpretable and versatile machine learning approach for oocyte phenotyping
dc:date	2022
Digital Object Identifier (DOI)	10.1242/jcs.260281

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